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Spring + Neo4j
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The Spring Data Neo4j project applies Spring Data concepts to the development of solutions using the Neo4j graph data store. We provide "repositories" as a high-level abstraction for storing and querying documents.

The next section provides some basic introduction to Spring and Graph databases.

The Spring Data Commons section then describes the common foundation of all Spring Data projects: the repositories. This part is taken from from SD commons project and may include examples from other persistence type such as JPA.

The rest of the document describes the Spring Data Neo4j features and specifics. It includes the Spring Data Neo4j reference, and the reference for Neo4j-OGM, on which SDN is based on. It assumes the user is familiar with the Neo4j graph database as well as Spring concepts.

1. Spring and Spring Data

Spring Data uses Spring framework’s core functionality, such as the IoC container, type conversion system, expression language, JMX integration, and portable DAO exception hierarchy. While it is not important to know the Spring APIs, understanding the concepts behind them is. At a minimum, the idea behind IoC should be familiar for whatever IoC container you choose to use.

The core functionality of the Neo4j support can be used directly, through the Neo4j-Session. This class corresponds to the Hibernate Session or JPA EntityManager.

To learn more about Spring, you can refer to the comprehensive documentation that explains in detail the Spring Framework. There are a lot of articles, blog entries and books on the matter - take a look at the Spring framework home page for more information.

2. NoSQL and Graph databases

A graph database is a storage engine that is specialised in storing and retrieving vast networks of information. It efficiently stores data as nodes with relationships to other or even the same nodes, thus allowing high-performance retrieval and querying of those structures. Properties can be added to both nodes and relationships. Nodes can be labelled by zero or more labels, relationships are always directed and named.

Graph databases are well suited for storing most kinds of domain models. In almost all domains, there are certain things connected to other things. In most other modelling approaches, the relationships between things are reduced to a single link without identity and attributes. Graph databases allow to keep the rich relationships that originate from the domain equally well-represented in the database without resorting to also modelling the relationships as "things". There is very little "impedance mismatch" when putting real-life domains into a graph database.

2.1. Introducing Neo4j

Neo4j is an open source NoSQL graph database. It is a fully transactional database (ACID) that stores data structured as graphs consisting of nodes, connected by relationships. Inspired by the structure of the real world, it allows for high query performance on complex data, while remaining intuitive and simple for the developer.

The starting point for learning about Neo4j is neo4j.com. Here is a list of useful resources:

3. Requirements

Spring Data Neo4j 5.1.x at minimum, requires:

  • JDK Version 8 and above.

  • Neo4j Graph Database 3.4 and above.

  • Spring Framework 5.2.14.RELEASE and above.

If you plan on altering the version of the Neo4j-OGM make sure it is a 3.1.0+ release, fitting into the matrix of compatible versions.

4. Additional Resources

4.2. Getting Help & give feedback

If you encounter issues, you can use the templates for reporting issues: https://github.com/neo4j-examples/neo4j-sdn-ogm-issue-report-template. If you are looking for advice, here are some more resources:

If you are new to Spring as well as to Spring Data, look for information about Spring projects.

5. New & Noteworthy

5.1. What’s new in Spring Data Neo4j 5.1.0

  • Support for SpEL expressions inside @Query annotation.

  • Support for optimistic locking using an @Version field.

  • Support for persistence constructors: No need for default constructors any more.

  • Methods annotated with @PostLoad now longer need to be public, they can be any of package protected, private and protected, thus allowing for a better design of your Domain that encapsulates your model.

  • Support the IgnoreCase flag: Derived queries can be case insensitive without resorting to regular expressions or custom queries.

  • Derived queries can traverse relationships and thus support nested properties several levels deep.

  • Full support for using multiple Neo4j-Server instances in one SDN-module allows you to use as many repository packages as you like using different connections and target domain packages.

  • Prevent eager initialization of beans needed for repository infrastructure.

  • @UseBookmark can now be used in custom, composed annotations.

  • Composable repositories are now supported in a CDI context.

5.2. What’s new in Spring Data Neo4j 5.0.0

  • SDN 5.x is designed to work with Java 8, Neo4j 3.1+, Spring 5 and Spring Boot 2.x.

  • Bolt is now the default database protocol.

  • For simplicity, annotations are now only supported on entity attributes, no more on accessors.

  • New id management ; database ids are not mandatory anymore.

  • Smarter deep querying based on domain model structure.

  • Dynamic properties allow mapping in Map structures.

  • Projections support.

  • Improved causal cluster support and bookmark management.

  • More flexible configuration.

  • Better Java 8 support : all type queries can now return stream results and Optional. Better date / time management.

  • Internal metadata handling has been refactored for better reliability.

  • Auditing support (since 5.0.1)

When migrating from 4.x, please see the migration guide.

6. Dependencies

Due to the different inception dates of individual Spring Data modules, most of them carry different major and minor version numbers. The easiest way to find compatible ones is to rely on the Spring Data Release Train BOM that we ship with the compatible versions defined. In a Maven project, you would declare this dependency in the <dependencyManagement /> section of your POM as follows:

Example 1. Using the Spring Data release train BOM

The current release train version is Neumann-SR9. The train names ascend alphabetically and the currently available trains are listed here. The version name follows the following pattern: ${name}-${release}, where release can be one of the following:

  • BUILD-SNAPSHOT: Current snapshots

  • M1, M2, and so on: Milestones

  • RC1, RC2, and so on: Release candidates

  • RELEASE: GA release

  • SR1, SR2, and so on: Service releases

You can find a working example of using the BOMs in our Spring Data examples repository. With that in place, you can declare the Spring Data modules you would like to use without a version in the <dependencies /> block, as follows:

Example 2. Declaring a dependency to a Spring Data module

6.1. Dependency Management with Spring Boot

Spring Boot selects a recent version of Spring Data modules for you. If you still want to upgrade to a newer version, set the spring-data-releasetrain.version property to the train name and iteration you would like to use.

6.2. Spring Framework

The current version of Spring Data modules require Spring Framework 5.2.14.RELEASE or better. The modules might also work with an older bugfix version of that minor version. However, using the most recent version within that generation is highly recommended. :spring-framework-docs: https://docs.spring.io/spring/docs/5.2.14.RELEASE/spring-framework-reference :spring-framework-javadoc: https://docs.spring.io/spring/docs/5.2.14.RELEASE/javadoc-api

7. Working with Spring Data Repositories

The goal of the Spring Data repository abstraction is to significantly reduce the amount of boilerplate code required to implement data access layers for various persistence stores.

Spring Data repository documentation and your module

This chapter explains the core concepts and interfaces of Spring Data repositories. The information in this chapter is pulled from the Spring Data Commons module. It uses the configuration and code samples for the Java Persistence API (JPA) module. You should adapt the XML namespace declaration and the types to be extended to the equivalents of the particular module that you use. “Namespace reference” covers XML configuration, which is supported across all Spring Data modules that support the repository API. “Repository query keywords” covers the query method keywords supported by the repository abstraction in general. For detailed information on the specific features of your module, see the chapter on that module of this document.

7.1. Core concepts

The central interface in the Spring Data repository abstraction is Repository. It takes the domain class to manage as well as the ID type of the domain class as type arguments. This interface acts primarily as a marker interface to capture the types to work with and to help you to discover interfaces that extend this one. The CrudRepository interface provides sophisticated CRUD functionality for the entity class that is being managed.

Example 3. CrudRepository Interface
public interface CrudRepository<T, ID> extends Repository<T, ID> {

  <S extends T> S save(S entity);      (1)

  Optional<T> findById(ID primaryKey); (2)

  Iterable<T> findAll();               (3)

  long count();                        (4)

  void delete(T entity);               (5)

  boolean existsById(ID primaryKey);   (6)

  // … more functionality omitted.
1 Saves the given entity.
2 Returns the entity identified by the given ID.
3 Returns all entities.
4 Returns the number of entities.
5 Deletes the given entity.
6 Indicates whether an entity with the given ID exists.
We also provide persistence technology-specific abstractions, such as JpaRepository or MongoRepository. Those interfaces extend CrudRepository and expose the capabilities of the underlying persistence technology in addition to the rather generic persistence technology-agnostic interfaces such as CrudRepository.

On top of the CrudRepository, there is a PagingAndSortingRepository abstraction that adds additional methods to ease paginated access to entities:

Example 4. PagingAndSortingRepository interface
public interface PagingAndSortingRepository<T, ID> extends CrudRepository<T, ID> {

  Iterable<T> findAll(Sort sort);

  Page<T> findAll(Pageable pageable);

To access the second page of User by a page size of 20, you could do something like the following:

PagingAndSortingRepository<User, Long> repository = // … get access to a bean
Page<User> users = repository.findAll(PageRequest.of(1, 20));

In addition to query methods, query derivation for both count and delete queries is available. The following list shows the interface definition for a derived count query:

Example 5. Derived Count Query
interface UserRepository extends CrudRepository<User, Long> {

  long countByLastname(String lastname);

The following listing shows the interface definition for a derived delete query:

Example 6. Derived Delete Query
interface UserRepository extends CrudRepository<User, Long> {

  long deleteByLastname(String lastname);

  List<User> removeByLastname(String lastname);

7.2. Query Methods

Standard CRUD functionality repositories usually have queries on the underlying datastore. With Spring Data, declaring those queries becomes a four-step process:

  1. Declare an interface extending Repository or one of its subinterfaces and type it to the domain class and ID type that it should handle, as shown in the following example:

    interface PersonRepository extends Repository<Person, Long> { … }
  2. Declare query methods on the interface.

    interface PersonRepository extends Repository<Person, Long> {
      List<Person> findByLastname(String lastname);
  3. Set up Spring to create proxy instances for those interfaces, either with JavaConfig or with XML configuration.

    1. To use Java configuration, create a class similar to the following:

      import org.springframework.data.jpa.repository.config.EnableJpaRepositories;
      class Config { … }
    2. To use XML configuration, define a bean similar to the following:

      <?xml version="1.0" encoding="UTF-8"?>
      <beans xmlns="http://www.springframework.org/schema/beans"
         <jpa:repositories base-package="com.acme.repositories"/>

      The JPA namespace is used in this example. If you use the repository abstraction for any other store, you need to change this to the appropriate namespace declaration of your store module. In other words, you should exchange jpa in favor of, for example, mongodb.

      Also, note that the JavaConfig variant does not configure a package explicitly, because the package of the annotated class is used by default. To customize the package to scan, use one of the basePackage… attributes of the data-store-specific repository’s @Enable${store}Repositories-annotation.

  4. Inject the repository instance and use it, as shown in the following example:

    class SomeClient {
      private final PersonRepository repository;
      SomeClient(PersonRepository repository) {
        this.repository = repository;
      void doSomething() {
        List<Person> persons = repository.findByLastname("Matthews");

The sections that follow explain each step in detail:

7.3. Defining Repository Interfaces

To define a repository interface, you first need to define a domain class-specific repository interface. The interface must extend Repository and be typed to the domain class and an ID type. If you want to expose CRUD methods for that domain type, extend CrudRepository instead of Repository.

7.3.1. Fine-tuning Repository Definition

Typically, your repository interface extends Repository, CrudRepository, or PagingAndSortingRepository. Alternatively, if you do not want to extend Spring Data interfaces, you can also annotate your repository interface with @RepositoryDefinition. Extending CrudRepository exposes a complete set of methods to manipulate your entities. If you prefer to be selective about the methods being exposed, copy the methods you want to expose from CrudRepository into your domain repository.

Doing so lets you define your own abstractions on top of the provided Spring Data Repositories functionality.

The following example shows how to selectively expose CRUD methods (findById and save, in this case):

Example 7. Selectively exposing CRUD methods
interface MyBaseRepository<T, ID> extends Repository<T, ID> {

  Optional<T> findById(ID id);

  <S extends T> S save(S entity);

interface UserRepository extends MyBaseRepository<User, Long> {
  User findByEmailAddress(EmailAddress emailAddress);

In the prior example, you defined a common base interface for all your domain repositories and exposed findById(…) as well as save(…).These methods are routed into the base repository implementation of the store of your choice provided by Spring Data (for example, if you use JPA, the implementation is SimpleJpaRepository), because they match the method signatures in CrudRepository. So the UserRepository can now save users, find individual users by ID, and trigger a query to find Users by email address.

The intermediate repository interface is annotated with @NoRepositoryBean. Make sure you add that annotation to all repository interfaces for which Spring Data should not create instances at runtime.

7.3.2. Using Repositories with Multiple Spring Data Modules

Using a unique Spring Data module in your application makes things simple, because all repository interfaces in the defined scope are bound to the Spring Data module. Sometimes, applications require using more than one Spring Data module. In such cases, a repository definition must distinguish between persistence technologies. When it detects multiple repository factories on the class path, Spring Data enters strict repository configuration mode. Strict configuration uses details on the repository or the domain class to decide about Spring Data module binding for a repository definition:

  1. If the repository definition extends the module-specific repository, it is a valid candidate for the particular Spring Data module.

  2. If the domain class is annotated with the module-specific type annotation, it is a valid candidate for the particular Spring Data module. Spring Data modules accept either third-party annotations (such as JPA’s @Entity) or provide their own annotations (such as @Document for Spring Data MongoDB and Spring Data Elasticsearch).

The following example shows a repository that uses module-specific interfaces (JPA in this case):

Example 8. Repository definitions using module-specific interfaces
interface MyRepository extends JpaRepository<User, Long> { }

interface MyBaseRepository<T, ID> extends JpaRepository<T, ID> { … }

interface UserRepository extends MyBaseRepository<User, Long> { … }

MyRepository and UserRepository extend JpaRepository in their type hierarchy. They are valid candidates for the Spring Data JPA module.

The following example shows a repository that uses generic interfaces:

Example 9. Repository definitions using generic interfaces
interface AmbiguousRepository extends Repository<User, Long> { … }

interface MyBaseRepository<T, ID> extends CrudRepository<T, ID> { … }

interface AmbiguousUserRepository extends MyBaseRepository<User, Long> { … }

AmbiguousRepository and AmbiguousUserRepository extend only Repository and CrudRepository in their type hierarchy. While this is fine when using a unique Spring Data module, multiple modules cannot distinguish to which particular Spring Data these repositories should be bound.

The following example shows a repository that uses domain classes with annotations:

Example 10. Repository definitions using domain classes with annotations
interface PersonRepository extends Repository<Person, Long> { … }

class Person { … }

interface UserRepository extends Repository<User, Long> { … }

class User { … }

PersonRepository references Person, which is annotated with the JPA @Entity annotation, so this repository clearly belongs to Spring Data JPA. UserRepository references User, which is annotated with Spring Data MongoDB’s @Document annotation.

The following bad example shows a repository that uses domain classes with mixed annotations:

Example 11. Repository definitions using domain classes with mixed annotations
interface JpaPersonRepository extends Repository<Person, Long> { … }

interface MongoDBPersonRepository extends Repository<Person, Long> { … }

class Person { … }

This example shows a domain class using both JPA and Spring Data MongoDB annotations. It defines two repositories, JpaPersonRepository and MongoDBPersonRepository. One is intended for JPA and the other for MongoDB usage. Spring Data is no longer able to tell the repositories apart, which leads to undefined behavior.

Repository type details and distinguishing domain class annotations are used for strict repository configuration to identify repository candidates for a particular Spring Data module. Using multiple persistence technology-specific annotations on the same domain type is possible and enables reuse of domain types across multiple persistence technologies. However, Spring Data can then no longer determine a unique module with which to bind the repository.

The last way to distinguish repositories is by scoping repository base packages. Base packages define the starting points for scanning for repository interface definitions, which implies having repository definitions located in the appropriate packages. By default, annotation-driven configuration uses the package of the configuration class. The base package in XML-based configuration is mandatory.

The following example shows annotation-driven configuration of base packages:

Example 12. Annotation-driven configuration of base packages
@EnableJpaRepositories(basePackages = "com.acme.repositories.jpa")
@EnableMongoRepositories(basePackages = "com.acme.repositories.mongo")
class Configuration { … }

7.4. Defining Query Methods

The repository proxy has two ways to derive a store-specific query from the method name:

  • By deriving the query from the method name directly.

  • By using a manually defined query.

Available options depend on the actual store. However, there must be a strategy that decides what actual query is created. The next section describes the available options.

7.4.1. Query Lookup Strategies

The following strategies are available for the repository infrastructure to resolve the query. With XML configuration, you can configure the strategy at the namespace through the query-lookup-strategy attribute. For Java configuration, you can use the queryLookupStrategy attribute of the Enable${store}Repositories annotation. Some strategies may not be supported for particular datastores.

  • CREATE attempts to construct a store-specific query from the query method name. The general approach is to remove a given set of well known prefixes from the method name and parse the rest of the method. You can read more about query construction in “Query Creation”.

  • USE_DECLARED_QUERY tries to find a declared query and throws an exception if it cannot find one. The query can be defined by an annotation somewhere or declared by other means. See the documentation of the specific store to find available options for that store. If the repository infrastructure does not find a declared query for the method at bootstrap time, it fails.

  • CREATE_IF_NOT_FOUND (the default) combines CREATE and USE_DECLARED_QUERY. It looks up a declared query first, and, if no declared query is found, it creates a custom method name-based query. This is the default lookup strategy and, thus, is used if you do not configure anything explicitly. It allows quick query definition by method names but also custom-tuning of these queries by introducing declared queries as needed.

7.4.2. Query Creation

The query builder mechanism built into the Spring Data repository infrastructure is useful for building constraining queries over entities of the repository.

The following example shows how to create a number of queries:

Example 13. Query creation from method names
interface PersonRepository extends Repository<Person, Long> {

  List<Person> findByEmailAddressAndLastname(EmailAddress emailAddress, String lastname);

  // Enables the distinct flag for the query
  List<Person> findDistinctPeopleByLastnameOrFirstname(String lastname, String firstname);
  List<Person> findPeopleDistinctByLastnameOrFirstname(String lastname, String firstname);

  // Enabling ignoring case for an individual property
  List<Person> findByLastnameIgnoreCase(String lastname);
  // Enabling ignoring case for all suitable properties
  List<Person> findByLastnameAndFirstnameAllIgnoreCase(String lastname, String firstname);

  // Enabling static ORDER BY for a query
  List<Person> findByLastnameOrderByFirstnameAsc(String lastname);
  List<Person> findByLastnameOrderByFirstnameDesc(String lastname);

Parsing query method names is divided into subject and predicate. The first part (find…By, exists…By) defines the subject of the query, the second part forms the predicate. The introducing clause (subject) can contain further expressions. Any text between find (or other introducing keywords) and By is considered to be descriptive unless using one of the result-limiting keywords such as a Distinct to set a distinct flag on the query to be created or Top/First to limit query results.

The appendix contains the full list of query method subject keywords and query method predicate keywords including sorting and letter-casing modifiers. However, the first By acts as a delimiter to indicate the start of the actual criteria predicate. At a very basic level, you can define conditions on entity properties and concatenate them with And and Or.

The actual result of parsing the method depends on the persistence store for which you create the query. However, there are some general things to notice:

  • The expressions are usually property traversals combined with operators that can be concatenated. You can combine property expressions with AND and OR. You also get support for operators such as Between, LessThan, GreaterThan, and Like for the property expressions. The supported operators can vary by datastore, so consult the appropriate part of your reference documentation.

  • The method parser supports setting an IgnoreCase flag for individual properties (for example, findByLastnameIgnoreCase(…)) or for all properties of a type that supports ignoring case (usually String instances — for example, findByLastnameAndFirstnameAllIgnoreCase(…)). Whether ignoring cases is supported may vary by store, so consult the relevant sections in the reference documentation for the store-specific query method.

  • You can apply static ordering by appending an OrderBy clause to the query method that references a property and by providing a sorting direction (Asc or Desc). To create a query method that supports dynamic sorting, see “Special parameter handling”.

7.4.3. Property Expressions

Property expressions can refer only to a direct property of the managed entity, as shown in the preceding example. At query creation time, you already make sure that the parsed property is a property of the managed domain class. However, you can also define constraints by traversing nested properties. Consider the following method signature:

List<Person> findByAddressZipCode(ZipCode zipCode);

Assume a Person has an Address with a ZipCode. In that case, the method creates the x.address.zipCode property traversal. The resolution algorithm starts by interpreting the entire part (AddressZipCode) as the property and checks the domain class for a property with that name (uncapitalized). If the algorithm succeeds, it uses that property. If not, the algorithm splits up the source at the camel-case parts from the right side into a head and a tail and tries to find the corresponding property — in our example, AddressZip and Code. If the algorithm finds a property with that head, it takes the tail and continues building the tree down from there, splitting the tail up in the way just described. If the first split does not match, the algorithm moves the split point to the left (Address, ZipCode) and continues.

Although this should work for most cases, it is possible for the algorithm to select the wrong property. Suppose the Person class has an addressZip property as well. The algorithm would match in the first split round already, choose the wrong property, and fail (as the type of addressZip probably has no code property).

To resolve this ambiguity you can use _ inside your method name to manually define traversal points. So our method name would be as follows:

List<Person> findByAddress_ZipCode(ZipCode zipCode);

Because we treat the underscore character as a reserved character, we strongly advise following standard Java naming conventions (that is, not using underscores in property names but using camel case instead).

7.4.4. Special parameter handling

To handle parameters in your query, define method parameters as already seen in the preceding examples. Besides that, the infrastructure recognizes certain specific types like Pageable and Sort, to apply pagination and sorting to your queries dynamically. The following example demonstrates these features:

Example 14. Using Pageable, Slice, and Sort in query methods
Page<User> findByLastname(String lastname, Pageable pageable);

Slice<User> findByLastname(String lastname, Pageable pageable);

List<User> findByLastname(String lastname, Sort sort);

List<User> findByLastname(String lastname, Pageable pageable);
APIs taking Sort and Pageable expect non-null values to be handed into methods. If you do not want to apply any sorting or pagination, use Sort.unsorted() and Pageable.unpaged().

The first method lets you pass an org.springframework.data.domain.Pageable instance to the query method to dynamically add paging to your statically defined query. A Page knows about the total number of elements and pages available. It does so by the infrastructure triggering a count query to calculate the overall number. As this might be expensive (depending on the store used), you can instead return a Slice. A Slice knows only about whether a next Slice is available, which might be sufficient when walking through a larger result set.

Sorting options are handled through the Pageable instance, too. If you need only sorting, add an org.springframework.data.domain.Sort parameter to your method. As you can see, returning a List is also possible. In this case, the additional metadata required to build the actual Page instance is not created (which, in turn, means that the additional count query that would have been necessary is not issued). Rather, it restricts the query to look up only the given range of entities.

To find out how many pages you get for an entire query, you have to trigger an additional count query. By default, this query is derived from the query you actually trigger.
Paging and Sorting

You can define simple sorting expressions by using property names. You can concatenate expressions to collect multiple criteria into one expression.

Example 15. Defining sort expressions
Sort sort = Sort.by("firstname").ascending()

For a more type-safe way to define sort expressions, start with the type for which to define the sort expression and use method references to define the properties on which to sort.

Example 16. Defining sort expressions by using the type-safe API
TypedSort<Person> person = Sort.sort(Person.class);

Sort sort = person.by(Person::getFirstname).ascending()
TypedSort.by(…) makes use of runtime proxies by (typically) using CGlib, which may interfere with native image compilation when using tools such as Graal VM Native.

If your store implementation supports Querydsl, you can also use the generated metamodel types to define sort expressions:

Example 17. Defining sort expressions by using the Querydsl API
QSort sort = QSort.by(QPerson.firstname.asc())

7.4.5. Limiting Query Results

You can limit the results of query methods by using the first or top keywords, which you can use interchangeably. You can append an optional numeric value to top or first to specify the maximum result size to be returned. If the number is left out, a result size of 1 is assumed. The following example shows how to limit the query size:

Example 18. Limiting the result size of a query with Top and First
User findFirstByOrderByLastnameAsc();

User findTopByOrderByAgeDesc();

Page<User> queryFirst10ByLastname(String lastname, Pageable pageable);

Slice<User> findTop3ByLastname(String lastname, Pageable pageable);

List<User> findFirst10ByLastname(String lastname, Sort sort);

List<User> findTop10ByLastname(String lastname, Pageable pageable);

The limiting expressions also support the Distinct keyword for datastores that support distinct queries. Also, for the queries that limit the result set to one instance, wrapping the result into with the Optional keyword is supported.

If pagination or slicing is applied to a limiting query pagination (and the calculation of the number of available pages), it is applied within the limited result.

Limiting the results in combination with dynamic sorting by using a Sort parameter lets you express query methods for the 'K' smallest as well as for the 'K' biggest elements.

7.4.6. Repository Methods Returning Collections or Iterables

Query methods that return multiple results can use standard Java Iterable, List, and Set. Beyond that, we support returning Spring Data’s Streamable, a custom extension of Iterable, as well as collection types provided by Vavr. Refer to the appendix explaining all possible query method return types.

Using Streamable as Query Method Return Type

You can use Streamable as alternative to Iterable or any collection type. It provides convenience methods to access a non-parallel Stream (missing from Iterable) and the ability to directly ….filter(…) and ….map(…) over the elements and concatenate the Streamable to others:

Example 19. Using Streamable to combine query method results
interface PersonRepository extends Repository<Person, Long> {
  Streamable<Person> findByFirstnameContaining(String firstname);
  Streamable<Person> findByLastnameContaining(String lastname);

Streamable<Person> result = repository.findByFirstnameContaining("av")
Returning Custom Streamable Wrapper Types

Providing dedicated wrapper types for collections is a commonly used pattern to provide an API for a query result that returns multiple elements. Usually, these types are used by invoking a repository method returning a collection-like type and creating an instance of the wrapper type manually. You can avoid that additional step as Spring Data lets you use these wrapper types as query method return types if they meet the following criteria:

  1. The type implements Streamable.

  2. The type exposes either a constructor or a static factory method named of(…) or valueOf(…) that takes Streamable as an argument.

The following listing shows an example:

class Product {                                         (1)
  MonetaryAmount getPrice() { … }

@RequiredArgConstructor(staticName = "of")
class Products implements Streamable<Product> {         (2)

  private Streamable<Product> streamable;

  public MonetaryAmount getTotal() {                    (3)
    return streamable.stream()
      .reduce(Money.of(0), MonetaryAmount::add);

  public Iterator<Product> iterator() {                 (4)
    return streamable.iterator();

interface ProductRepository implements Repository<Product, Long> {
  Products findAllByDescriptionContaining(String text); (5)
1 A Product entity that exposes API to access the product’s price.
2 A wrapper type for a Streamable<Product> that can be constructed by using Products.of(…) (factory method created with the Lombok annotation). A standard constructor taking the Streamable<Product> will do as well.
3 The wrapper type exposes an additional API, calculating new values on the Streamable<Product>.
4 Implement the Streamable interface and delegate to the actual result.
5 That wrapper type Products can be used directly as a query method return type. You do not need to return Streamable<Product> and manually wrap it after the query in the repository client.
Support for Vavr Collections

Vavr is a library that embraces functional programming concepts in Java. It ships with a custom set of collection types that you can use as query method return types, as the following table shows:

Vavr collection type Used Vavr implementation type Valid Java source types










You can use the types in the first column (or subtypes thereof) as query method return types and get the types in the second column used as implementation type, depending on the Java type of the actual query result (third column). Alternatively, you can declare Traversable (the Vavr Iterable equivalent), and we then derive the implementation class from the actual return value. That is, a java.util.List is turned into a Vavr List or Seq, a java.util.Set becomes a Vavr LinkedHashSet Set, and so on.

7.4.7. Null Handling of Repository Methods

As of Spring Data 2.0, repository CRUD methods that return an individual aggregate instance use Java 8’s Optional to indicate the potential absence of a value. Besides that, Spring Data supports returning the following wrapper types on query methods:

  • com.google.common.base.Optional

  • scala.Option

  • io.vavr.control.Option

Alternatively, query methods can choose not to use a wrapper type at all. The absence of a query result is then indicated by returning null. Repository methods returning collections, collection alternatives, wrappers, and streams are guaranteed never to return null but rather the corresponding empty representation. See “Repository query return types” for details.

Nullability Annotations

You can express nullability constraints for repository methods by using {spring-framework-docs}/core.html#null-safety[Spring Framework’s nullability annotations]. They provide a tooling-friendly approach and opt-in null checks during runtime, as follows:

  • {spring-framework-javadoc}/org/springframework/lang/NonNullApi.html[@NonNullApi]: Used on the package level to declare that the default behavior for parameters and return values is, respectively, neither to accept nor to produce null values.

  • {spring-framework-javadoc}/org/springframework/lang/NonNull.html[@NonNull]: Used on a parameter or return value that must not be null (not needed on a parameter and return value where @NonNullApi applies).

  • {spring-framework-javadoc}/org/springframework/lang/Nullable.html[@Nullable]: Used on a parameter or return value that can be null.

Spring annotations are meta-annotated with JSR 305 annotations (a dormant but widely used JSR). JSR 305 meta-annotations let tooling vendors (such as IDEA, Eclipse, and Kotlin) provide null-safety support in a generic way, without having to hard-code support for Spring annotations. To enable runtime checking of nullability constraints for query methods, you need to activate non-nullability on the package level by using Spring’s @NonNullApi in package-info.java, as shown in the following example:

Example 20. Declaring Non-nullability in package-info.java
package com.acme;

Once non-null defaulting is in place, repository query method invocations get validated at runtime for nullability constraints. If a query result violates the defined constraint, an exception is thrown. This happens when the method would return null but is declared as non-nullable (the default with the annotation defined on the package in which the repository resides). If you want to opt-in to nullable results again, selectively use @Nullable on individual methods. Using the result wrapper types mentioned at the start of this section continues to work as expected: an empty result is translated into the value that represents absence.

The following example shows a number of the techniques just described:

Example 21. Using different nullability constraints
package com.acme;                                                       (1)

import org.springframework.lang.Nullable;

interface UserRepository extends Repository<User, Long> {

  User getByEmailAddress(EmailAddress emailAddress);                    (2)

  User findByEmailAddress(@Nullable EmailAddress emailAdress);          (3)

  Optional<User> findOptionalByEmailAddress(EmailAddress emailAddress); (4)
1 The repository resides in a package (or sub-package) for which we have defined non-null behavior.
2 Throws an EmptyResultDataAccessException when the query does not produce a result. Throws an IllegalArgumentException when the emailAddress handed to the method is null.
3 Returns null when the query does not produce a result. Also accepts null as the value for emailAddress.
4 Returns Optional.empty() when the query does not produce a result. Throws an IllegalArgumentException when the emailAddress handed to the method is null.
Nullability in Kotlin-based Repositories

Kotlin has the definition of nullability constraints baked into the language. Kotlin code compiles to bytecode, which does not express nullability constraints through method signatures but rather through compiled-in metadata. Make sure to include the kotlin-reflect JAR in your project to enable introspection of Kotlin’s nullability constraints. Spring Data repositories use the language mechanism to define those constraints to apply the same runtime checks, as follows:

Example 22. Using nullability constraints on Kotlin repositories
interface UserRepository : Repository<User, String> {

  fun findByUsername(username: String): User     (1)

  fun findByFirstname(firstname: String?): User? (2)
1 The method defines both the parameter and the result as non-nullable (the Kotlin default). The Kotlin compiler rejects method invocations that pass null to the method. If the query yields an empty result, an EmptyResultDataAccessException is thrown.
2 This method accepts null for the firstname parameter and returns null if the query does not produce a result.

7.4.8. Streaming Query Results

You can process the results of query methods incrementally by using a Java 8 Stream<T> as the return type. Instead of wrapping the query results in a Stream, data store-specific methods are used to perform the streaming, as shown in the following example:

Example 23. Stream the result of a query with Java 8 Stream<T>
@Query("select u from User u")
Stream<User> findAllByCustomQueryAndStream();

Stream<User> readAllByFirstnameNotNull();

@Query("select u from User u")
Stream<User> streamAllPaged(Pageable pageable);
A Stream potentially wraps underlying data store-specific resources and must, therefore, be closed after usage. You can either manually close the Stream by using the close() method or by using a Java 7 try-with-resources block, as shown in the following example:
Example 24. Working with a Stream<T> result in a try-with-resources block
try (Stream<User> stream = repository.findAllByCustomQueryAndStream()) {
Not all Spring Data modules currently support Stream<T> as a return type.

7.4.9. Asynchronous Query Results

You can run repository queries asynchronously by using {spring-framework-docs}/integration.html#scheduling[Spring’s asynchronous method running capability]. This means the method returns immediately upon invocation while the actual query occurs in a task that has been submitted to a Spring TaskExecutor. Asynchronous queries differ from reactive queries and should not be mixed. See the store-specific documentation for more details on reactive support. The following example shows a number of asynchronous queries:

Future<User> findByFirstname(String firstname);               (1)

CompletableFuture<User> findOneByFirstname(String firstname); (2)

ListenableFuture<User> findOneByLastname(String lastname);    (3)
1 Use java.util.concurrent.Future as the return type.
2 Use a Java 8 java.util.concurrent.CompletableFuture as the return type.
3 Use a org.springframework.util.concurrent.ListenableFuture as the return type.

7.5. Creating Repository Instances

This section covers how to create instances and bean definitions for the defined repository interfaces. One way to do so is by using the Spring namespace that is shipped with each Spring Data module that supports the repository mechanism, although we generally recommend using Java configuration.

7.5.1. XML Configuration

Each Spring Data module includes a repositories element that lets you define a base package that Spring scans for you, as shown in the following example:

Example 25. Enabling Spring Data repositories via XML
<?xml version="1.0" encoding="UTF-8"?>
<beans:beans xmlns:beans="http://www.springframework.org/schema/beans"

  <repositories base-package="com.acme.repositories" />


In the preceding example, Spring is instructed to scan com.acme.repositories and all its sub-packages for interfaces extending Repository or one of its sub-interfaces. For each interface found, the infrastructure registers the persistence technology-specific FactoryBean to create the appropriate proxies that handle invocations of the query methods. Each bean is registered under a bean name that is derived from the interface name, so an interface of UserRepository would be registered under userRepository. The base-package attribute allows wildcards so that you can define a pattern of scanned packages.

Using Filters

By default, the infrastructure picks up every interface that extends the persistence technology-specific Repository sub-interface located under the configured base package and creates a bean instance for it. However, you might want more fine-grained control over which interfaces have bean instances created for them. To do so, use <include-filter /> and <exclude-filter /> elements inside the <repositories /> element. The semantics are exactly equivalent to the elements in Spring’s context namespace. For details, see the {spring-framework-docs}/core.html#beans-scanning-filters[Spring reference documentation] for these elements.

For example, to exclude certain interfaces from instantiation as repository beans, you could use the following configuration:

Example 26. Using exclude-filter element
<repositories base-package="com.acme.repositories">
  <context:exclude-filter type="regex" expression=".*SomeRepository" />

The preceding example excludes all interfaces ending in SomeRepository from being instantiated.

7.5.2. Java Configuration

You can also trigger the repository infrastructure by using a store-specific @Enable${store}Repositories annotation on a Java configuration class. For an introduction to Java-based configuration of the Spring container, see {spring-framework-docs}/core.html#beans-java[JavaConfig in the Spring reference documentation].

A sample configuration to enable Spring Data repositories resembles the following:

Example 27. Sample annotation-based repository configuration
class ApplicationConfiguration {

  EntityManagerFactory entityManagerFactory() {
    // …
The preceding example uses the JPA-specific annotation, which you would change according to the store module you actually use. The same applies to the definition of the EntityManagerFactory bean. See the sections covering the store-specific configuration.

7.5.3. Standalone Usage

You can also use the repository infrastructure outside of a Spring container — for example, in CDI environments. You still need some Spring libraries in your classpath, but, generally, you can set up repositories programmatically as well. The Spring Data modules that provide repository support ship with a persistence technology-specific RepositoryFactory that you can use, as follows:

Example 28. Standalone usage of the repository factory
RepositoryFactorySupport factory = … // Instantiate factory here
UserRepository repository = factory.getRepository(UserRepository.class);

7.6. Custom Implementations for Spring Data Repositories

This section covers repository customization and how fragments form a composite repository.

When a query method requires a different behavior or cannot be implemented by query derivation, you need to provide a custom implementation. Spring Data repositories let you provide custom repository code and integrate it with generic CRUD abstraction and query method functionality.

7.6.1. Customizing Individual Repositories

To enrich a repository with custom functionality, you must first define a fragment interface and an implementation for the custom functionality, as follows:

Example 29. Interface for custom repository functionality
interface CustomizedUserRepository {
  void someCustomMethod(User user);
Example 30. Implementation of custom repository functionality
class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

  public void someCustomMethod(User user) {
    // Your custom implementation
The most important part of the class name that corresponds to the fragment interface is the Impl postfix.

The implementation itself does not depend on Spring Data and can be a regular Spring bean. Consequently, you can use standard dependency injection behavior to inject references to other beans (such as a JdbcTemplate), take part in aspects, and so on.

Then you can let your repository interface extend the fragment interface, as follows:

Example 31. Changes to your repository interface
interface UserRepository extends CrudRepository<User, Long>, CustomizedUserRepository {

  // Declare query methods here

Extending the fragment interface with your repository interface combines the CRUD and custom functionality and makes it available to clients.

Spring Data repositories are implemented by using fragments that form a repository composition. Fragments are the base repository, functional aspects (such as QueryDsl), and custom interfaces along with their implementations. Each time you add an interface to your repository interface, you enhance the composition by adding a fragment. The base repository and repository aspect implementations are provided by each Spring Data module.

The following example shows custom interfaces and their implementations:

Example 32. Fragments with their implementations
interface HumanRepository {
  void someHumanMethod(User user);

class HumanRepositoryImpl implements HumanRepository {

  public void someHumanMethod(User user) {
    // Your custom implementation

interface ContactRepository {

  void someContactMethod(User user);

  User anotherContactMethod(User user);

class ContactRepositoryImpl implements ContactRepository {

  public void someContactMethod(User user) {
    // Your custom implementation

  public User anotherContactMethod(User user) {
    // Your custom implementation

The following example shows the interface for a custom repository that extends CrudRepository:

Example 33. Changes to your repository interface
interface UserRepository extends CrudRepository<User, Long>, HumanRepository, ContactRepository {

  // Declare query methods here

Repositories may be composed of multiple custom implementations that are imported in the order of their declaration. Custom implementations have a higher priority than the base implementation and repository aspects. This ordering lets you override base repository and aspect methods and resolves ambiguity if two fragments contribute the same method signature. Repository fragments are not limited to use in a single repository interface. Multiple repositories may use a fragment interface, letting you reuse customizations across different repositories.

The following example shows a repository fragment and its implementation:

Example 34. Fragments overriding save(…)
interface CustomizedSave<T> {
  <S extends T> S save(S entity);

class CustomizedSaveImpl<T> implements CustomizedSave<T> {

  public <S extends T> S save(S entity) {
    // Your custom implementation

The following example shows a repository that uses the preceding repository fragment:

Example 35. Customized repository interfaces
interface UserRepository extends CrudRepository<User, Long>, CustomizedSave<User> {

interface PersonRepository extends CrudRepository<Person, Long>, CustomizedSave<Person> {

If you use namespace configuration, the repository infrastructure tries to autodetect custom implementation fragments by scanning for classes below the package in which it found a repository. These classes need to follow the naming convention of appending the namespace element’s repository-impl-postfix attribute to the fragment interface name. This postfix defaults to Impl. The following example shows a repository that uses the default postfix and a repository that sets a custom value for the postfix:

Example 36. Configuration example
<repositories base-package="com.acme.repository" />

<repositories base-package="com.acme.repository" repository-impl-postfix="MyPostfix" />

The first configuration in the preceding example tries to look up a class called com.acme.repository.CustomizedUserRepositoryImpl to act as a custom repository implementation. The second example tries to look up com.acme.repository.CustomizedUserRepositoryMyPostfix.

Resolution of Ambiguity

If multiple implementations with matching class names are found in different packages, Spring Data uses the bean names to identify which one to use.

Given the following two custom implementations for the CustomizedUserRepository shown earlier, the first implementation is used. Its bean name is customizedUserRepositoryImpl, which matches that of the fragment interface (CustomizedUserRepository) plus the postfix Impl.

Example 37. Resolution of ambiguous implementations
package com.acme.impl.one;

class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

  // Your custom implementation
package com.acme.impl.two;

class CustomizedUserRepositoryImpl implements CustomizedUserRepository {

  // Your custom implementation

If you annotate the UserRepository interface with @Component("specialCustom"), the bean name plus Impl then matches the one defined for the repository implementation in com.acme.impl.two, and it is used instead of the first one.

Manual Wiring

If your custom implementation uses annotation-based configuration and autowiring only, the preceding approach shown works well, because it is treated as any other Spring bean. If your implementation fragment bean needs special wiring, you can declare the bean and name it according to the conventions described in the preceding section. The infrastructure then refers to the manually defined bean definition by name instead of creating one itself. The following example shows how to manually wire a custom implementation:

Example 38. Manual wiring of custom implementations
<repositories base-package="com.acme.repository" />

<beans:bean id="userRepositoryImpl" class="…">
  <!-- further configuration -->

7.6.2. Customize the Base Repository

The approach described in the preceding section requires customization of each repository interfaces when you want to customize the base repository behavior so that all repositories are affected. To instead change behavior for all repositories, you can create an implementation that extends the persistence technology-specific repository base class. This class then acts as a custom base class for the repository proxies, as shown in the following example:

Example 39. Custom repository base class
class MyRepositoryImpl<T, ID>
  extends SimpleJpaRepository<T, ID> {

  private final EntityManager entityManager;

  MyRepositoryImpl(JpaEntityInformation entityInformation,
                          EntityManager entityManager) {
    super(entityInformation, entityManager);

    // Keep the EntityManager around to used from the newly introduced methods.
    this.entityManager = entityManager;

  public <S extends T> S save(S entity) {
    // implementation goes here
The class needs to have a constructor of the super class which the store-specific repository factory implementation uses. If the repository base class has multiple constructors, override the one taking an EntityInformation plus a store specific infrastructure object (such as an EntityManager or a template class).

The final step is to make the Spring Data infrastructure aware of the customized repository base class. In Java configuration, you can do so by using the repositoryBaseClass attribute of the @Enable${store}Repositories annotation, as shown in the following example:

Example 40. Configuring a custom repository base class using JavaConfig
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }

A corresponding attribute is available in the XML namespace, as shown in the following example:

Example 41. Configuring a custom repository base class using XML
<repositories base-package="com.acme.repository"
     base-class="….MyRepositoryImpl" />

7.7. Publishing Events from Aggregate Roots

Entities managed by repositories are aggregate roots. In a Domain-Driven Design application, these aggregate roots usually publish domain events. Spring Data provides an annotation called @DomainEvents that you can use on a method of your aggregate root to make that publication as easy as possible, as shown in the following example:

Example 42. Exposing domain events from an aggregate root
class AnAggregateRoot {

    @DomainEvents (1)
    Collection<Object> domainEvents() {
        // … return events you want to get published here

    @AfterDomainEventPublication (2)
    void callbackMethod() {
       // … potentially clean up domain events list
1 The method that uses @DomainEvents can return either a single event instance or a collection of events. It must not take any arguments.
2 After all events have been published, we have a method annotated with @AfterDomainEventPublication. You can use it to potentially clean the list of events to be published (among other uses).

The methods are called every time one of a Spring Data repository’s save(…) methods is called.

7.8. Spring Data Extensions

This section documents a set of Spring Data extensions that enable Spring Data usage in a variety of contexts. Currently, most of the integration is targeted towards Spring MVC.

7.8.1. Querydsl Extension

Querydsl is a framework that enables the construction of statically typed SQL-like queries through its fluent API.

Several Spring Data modules offer integration with Querydsl through QuerydslPredicateExecutor, as the following example shows:

Example 43. QuerydslPredicateExecutor interface
public interface QuerydslPredicateExecutor<T> {

  Optional<T> findById(Predicate predicate);  (1)

  Iterable<T> findAll(Predicate predicate);   (2)

  long count(Predicate predicate);            (3)

  boolean exists(Predicate predicate);        (4)

  // … more functionality omitted.
1 Finds and returns a single entity matching the Predicate.
2 Finds and returns all entities matching the Predicate.
3 Returns the number of entities matching the Predicate.
4 Returns whether an entity that matches the Predicate exists.

To use the Querydsl support, extend QuerydslPredicateExecutor on your repository interface, as the following example shows:

Example 44. Querydsl integration on repositories
interface UserRepository extends CrudRepository<User, Long>, QuerydslPredicateExecutor<User> {

The preceding example lets you write type-safe queries by using Querydsl Predicate instances, as the following example shows:

Predicate predicate = user.firstname.equalsIgnoreCase("dave")


7.8.2. Web support

Spring Data modules that support the repository programming model ship with a variety of web support. The web related components require Spring MVC JARs to be on the classpath. Some of them even provide integration with Spring HATEOAS. In general, the integration support is enabled by using the @EnableSpringDataWebSupport annotation in your JavaConfig configuration class, as the following example shows:

Example 45. Enabling Spring Data web support
class WebConfiguration {}

The @EnableSpringDataWebSupport annotation registers a few components. We discuss those later in this section. It also detects Spring HATEOAS on the classpath and registers integration components (if present) for it as well.

Alternatively, if you use XML configuration, register either SpringDataWebConfiguration or HateoasAwareSpringDataWebConfiguration as Spring beans, as the following example shows (for SpringDataWebConfiguration):

Example 46. Enabling Spring Data web support in XML
<bean class="org.springframework.data.web.config.SpringDataWebConfiguration" />

<!-- If you use Spring HATEOAS, register this one *instead* of the former -->
<bean class="org.springframework.data.web.config.HateoasAwareSpringDataWebConfiguration" />
Basic Web Support

The configuration shown in the previous section registers a few basic components:

  • A Using the DomainClassConverter Class to let Spring MVC resolve instances of repository-managed domain classes from request parameters or path variables.

  • HandlerMethodArgumentResolver implementations to let Spring MVC resolve Pageable and Sort instances from request parameters.

  • Jackson Modules to de-/serialize types like Point and Distance, or store specific ones, depending on the Spring Data Module used.

Using the DomainClassConverter Class

The DomainClassConverter class lets you use domain types in your Spring MVC controller method signatures directly so that you need not manually lookup the instances through the repository, as the following example shows:

Example 47. A Spring MVC controller using domain types in method signatures
class UserController {

  String showUserForm(@PathVariable("id") User user, Model model) {

    model.addAttribute("user", user);
    return "userForm";

The method receives a User instance directly, and no further lookup is necessary. The instance can be resolved by letting Spring MVC convert the path variable into the id type of the domain class first and eventually access the instance through calling findById(…) on the repository instance registered for the domain type.

Currently, the repository has to implement CrudRepository to be eligible to be discovered for conversion.
HandlerMethodArgumentResolvers for Pageable and Sort

The configuration snippet shown in the previous section also registers a PageableHandlerMethodArgumentResolver as well as an instance of SortHandlerMethodArgumentResolver. The registration enables Pageable and Sort as valid controller method arguments, as the following example shows:

Example 48. Using Pageable as a controller method argument
class UserController {

  private final UserRepository repository;

  UserController(UserRepository repository) {
    this.repository = repository;

  String showUsers(Model model, Pageable pageable) {

    model.addAttribute("users", repository.findAll(pageable));
    return "users";

The preceding method signature causes Spring MVC try to derive a Pageable instance from the request parameters by using the following default configuration:

Table 1. Request parameters evaluated for Pageable instances


Page you want to retrieve. 0-indexed and defaults to 0.


Size of the page you want to retrieve. Defaults to 20.


Properties that should be sorted by in the format property,property(,ASC|DESC)(,IgnoreCase). The default sort direction is case-sensitive ascending. Use multiple sort parameters if you want to switch direction or case sensitivity — for example, ?sort=firstname&sort=lastname,asc&sort=city,ignorecase.

To customize this behavior, register a bean that implements the PageableHandlerMethodArgumentResolverCustomizer interface or the SortHandlerMethodArgumentResolverCustomizer interface, respectively. Its customize() method gets called, letting you change settings, as the following example shows:

@Bean SortHandlerMethodArgumentResolverCustomizer sortCustomizer() {
    return s -> s.setPropertyDelimiter("<-->");

If setting the properties of an existing MethodArgumentResolver is not sufficient for your purpose, extend either SpringDataWebConfiguration or the HATEOAS-enabled equivalent, override the pageableResolver() or sortResolver() methods, and import your customized configuration file instead of using the @Enable annotation.

If you need multiple Pageable or Sort instances to be resolved from the request (for multiple tables, for example), you can use Spring’s @Qualifier annotation to distinguish one from another. The request parameters then have to be prefixed with ${qualifier}_. The following example shows the resulting method signature:

String showUsers(Model model,
      @Qualifier("thing1") Pageable first,
      @Qualifier("thing2") Pageable second) { … }

You have to populate thing1_page, thing2_page, and so on.

The default Pageable passed into the method is equivalent to a PageRequest.of(0, 20), but you can customize it by using the @PageableDefault annotation on the Pageable parameter.

Hypermedia Support for Pageables

Spring HATEOAS ships with a representation model class (PagedResources) that allows enriching the content of a Page instance with the necessary Page metadata as well as links to let the clients easily navigate the pages. The conversion of a Page to a PagedResources is done by an implementation of the Spring HATEOAS ResourceAssembler interface, called the PagedResourcesAssembler. The following example shows how to use a PagedResourcesAssembler as a controller method argument:

Example 49. Using a PagedResourcesAssembler as controller method argument
class PersonController {

  @Autowired PersonRepository repository;

  @RequestMapping(value = "/persons", method = RequestMethod.GET)
  HttpEntity<PagedResources<Person>> persons(Pageable pageable,
    PagedResourcesAssembler assembler) {

    Page<Person> persons = repository.findAll(pageable);
    return new ResponseEntity<>(assembler.toResources(persons), HttpStatus.OK);

Enabling the configuration, as shown in the preceding example, lets the PagedResourcesAssembler be used as a controller method argument. Calling toResources(…) on it has the following effects:

  • The content of the Page becomes the content of the PagedResources instance.

  • The PagedResources object gets a PageMetadata instance attached, and it is populated with information from the Page and the underlying PageRequest.

  • The PagedResources may get prev and next links attached, depending on the page’s state. The links point to the URI to which the method maps. The pagination parameters added to the method match the setup of the PageableHandlerMethodArgumentResolver to make sure the links can be resolved later.

Assume we have 30 Person instances in the database. You can now trigger a request (GET http://localhost:8080/persons) and see output similar to the following:

{ "links" : [ { "rel" : "next",
                "href" : "http://localhost:8080/persons?page=1&size=20" }
  "content" : [
     … // 20 Person instances rendered here
  "pageMetadata" : {
    "size" : 20,
    "totalElements" : 30,
    "totalPages" : 2,
    "number" : 0

The assembler produced the correct URI and also picked up the default configuration to resolve the parameters into a Pageable for an upcoming request. This means that, if you change that configuration, the links automatically adhere to the change. By default, the assembler points to the controller method it was invoked in, but you can customize that by passing a custom Link to be used as base to build the pagination links, which overloads the PagedResourcesAssembler.toResource(…) method.

Spring Data Jackson Modules

The core module, and some of the store specific ones, ship with a set of Jackson Modules for types, like org.springframework.data.geo.Distance and org.springframework.data.geo.Point, used by the Spring Data domain.
Those Modules are imported once web support is enabled and com.fasterxml.jackson.databind.ObjectMapper is available.

During initialization SpringDataJacksonModules, like the SpringDataJacksonConfiguration, get picked up by the infrastructure, so that the declared com.fasterxml.jackson.databind.Modules are made available to the Jackson ObjectMapper.

Data binding mixins for the following domain types are registered by the common infrastructure.


The individual module may provide additional SpringDataJacksonModules.
Please refer to the store specific section for more details.

Web Databinding Support

You can use Spring Data projections (described in [projections]) to bind incoming request payloads by using either JSONPath expressions (requires Jayway JsonPath or XPath expressions (requires XmlBeam), as the following example shows:

Example 50. HTTP payload binding using JSONPath or XPath expressions
public interface UserPayload {

  String getFirstname();

  @JsonPath({ "$.lastname", "$.user.lastname" })
  String getLastname();

You can use the type shown in the preceding example as a Spring MVC handler method argument or by using ParameterizedTypeReference on one of methods of the RestTemplate. The preceding method declarations would try to find firstname anywhere in the given document. The lastname XML lookup is performed on the top-level of the incoming document. The JSON variant of that tries a top-level lastname first but also tries lastname nested in a user sub-document if the former does not return a value. That way, changes in the structure of the source document can be mitigated easily without having clients calling the exposed methods (usually a drawback of class-based payload binding).

Nested projections are supported as described in [projections]. If the method returns a complex, non-interface type, a Jackson ObjectMapper is used to map the final value.

For Spring MVC, the necessary converters are registered automatically as soon as @EnableSpringDataWebSupport is active and the required dependencies are available on the classpath. For usage with RestTemplate, register a ProjectingJackson2HttpMessageConverter (JSON) or XmlBeamHttpMessageConverter manually.

For more information, see the web projection example in the canonical Spring Data Examples repository.

Querydsl Web Support

For those stores that have QueryDSL integration, you can derive queries from the attributes contained in a Request query string.

Consider the following query string:


Given the User object from the previous examples, you can resolve a query string to the following value by using the QuerydslPredicateArgumentResolver, as follows:

The feature is automatically enabled, along with @EnableSpringDataWebSupport, when Querydsl is found on the classpath.

Adding a @QuerydslPredicate to the method signature provides a ready-to-use Predicate, which you can run by using the QuerydslPredicateExecutor.

Type information is typically resolved from the method’s return type. Since that information does not necessarily match the domain type, it might be a good idea to use the root attribute of QuerydslPredicate.

The following example shows how to use @QuerydslPredicate in a method signature:

class UserController {

  @Autowired UserRepository repository;

  @RequestMapping(value = "/", method = RequestMethod.GET)
  String index(Model model, @QuerydslPredicate(root = User.class) Predicate predicate,    (1)
          Pageable pageable, @RequestParam MultiValueMap<String, String> parameters) {

    model.addAttribute("users", repository.findAll(predicate, pageable));

    return "index";
1 Resolve query string arguments to matching Predicate for User.

The default binding is as follows:

  • Object on simple properties as eq.

  • Object on collection like properties as contains.

  • Collection on simple properties as in.

You can customize those bindings through the bindings attribute of @QuerydslPredicate or by making use of Java 8 default methods and adding the QuerydslBinderCustomizer method to the repository interface, as follows:

interface UserRepository extends CrudRepository<User, String>,
                                 QuerydslPredicateExecutor<User>,                (1)
                                 QuerydslBinderCustomizer<QUser> {               (2)

  default void customize(QuerydslBindings bindings, QUser user) {

    bindings.bind(user.username).first((path, value) -> path.contains(value))    (3)
      .first((StringPath path, String value) -> path.containsIgnoreCase(value)); (4)
    bindings.excluding(user.password);                                           (5)
1 QuerydslPredicateExecutor provides access to specific finder methods for Predicate.
2 QuerydslBinderCustomizer defined on the repository interface is automatically picked up and shortcuts @QuerydslPredicate(bindings=…​).
3 Define the binding for the username property to be a simple contains binding.
4 Define the default binding for String properties to be a case-insensitive contains match.
5 Exclude the password property from Predicate resolution.

7.8.3. Repository Populators

If you work with the Spring JDBC module, you are probably familiar with the support for populating a DataSource with SQL scripts. A similar abstraction is available on the repositories level, although it does not use SQL as the data definition language because it must be store-independent. Thus, the populators support XML (through Spring’s OXM abstraction) and JSON (through Jackson) to define data with which to populate the repositories.

Assume you have a file called data.json with the following content:

Example 51. Data defined in JSON
[ { "_class" : "com.acme.Person",
 "firstname" : "Dave",
  "lastname" : "Matthews" },
  { "_class" : "com.acme.Person",
 "firstname" : "Carter",
  "lastname" : "Beauford" } ]

You can populate your repositories by using the populator elements of the repository namespace provided in Spring Data Commons. To populate the preceding data to your PersonRepository, declare a populator similar to the following:

Example 52. Declaring a Jackson repository populator
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"

  <repository:jackson2-populator locations="classpath:data.json" />


The preceding declaration causes the data.json file to be read and deserialized by a Jackson ObjectMapper.

The type to which the JSON object is unmarshalled is determined by inspecting the _class attribute of the JSON document. The infrastructure eventually selects the appropriate repository to handle the object that was deserialized.

To instead use XML to define the data the repositories should be populated with, you can use the unmarshaller-populator element. You configure it to use one of the XML marshaller options available in Spring OXM. See the {spring-framework-docs}/data-access.html#oxm[Spring reference documentation] for details. The following example shows how to unmarshall a repository populator with JAXB:

Example 53. Declaring an unmarshalling repository populator (using JAXB)
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"

  <repository:unmarshaller-populator locations="classpath:data.json"
    unmarshaller-ref="unmarshaller" />

  <oxm:jaxb2-marshaller contextPath="com.acme" />


8. Auditing

8.1. Basics

Spring Data provides sophisticated support to transparently keep track of who created or changed an entity and when the change happened. To benefit from that functionality, you have to equip your entity classes with auditing metadata that can be defined either using annotations or by implementing an interface. Additionally, auditing has to be enabled either through Annotation configuration or XML configuration to register the required infrastructure components. Please refer to the store-specific section for configuration samples.

Applications that only track creation and modification dates do not need to specify an AuditorAware.

8.1.1. Annotation-based Auditing Metadata

We provide @CreatedBy and @LastModifiedBy to capture the user who created or modified the entity as well as @CreatedDate and @LastModifiedDate to capture when the change happened.

Example 54. An audited entity
class Customer {

  private User user;

  private Instant createdDate;

  // … further properties omitted

As you can see, the annotations can be applied selectively, depending on which information you want to capture. The annotations capturing when changes were made can be used on properties of type Joda-Time, DateTime, legacy Java Date and Calendar, JDK8 date and time types, and long or Long.

Auditing metadata does not necessarily need to live in the root level entity but can be added to an embedded one (depending on the actual store in use), as shown in the snipped below.

Example 55. Audit metadata in embedded entity
class Customer {

  private AuditMetadata auditingMetadata;

  // … further properties omitted

class AuditMetadata {

  private User user;

  private Instant createdDate;


8.1.2. Interface-based Auditing Metadata

In case you do not want to use annotations to define auditing metadata, you can let your domain class implement the Auditable interface. It exposes setter methods for all of the auditing properties.

There is also a convenience base class, AbstractAuditable, which you can extend to avoid the need to manually implement the interface methods. Doing so increases the coupling of your domain classes to Spring Data, which might be something you want to avoid. Usually, the annotation-based way of defining auditing metadata is preferred as it is less invasive and more flexible.

8.1.3. AuditorAware

In case you use either @CreatedBy or @LastModifiedBy, the auditing infrastructure somehow needs to become aware of the current principal. To do so, we provide an AuditorAware<T> SPI interface that you have to implement to tell the infrastructure who the current user or system interacting with the application is. The generic type T defines what type the properties annotated with @CreatedBy or @LastModifiedBy have to be.

The following example shows an implementation of the interface that uses Spring Security’s Authentication object:

Example 56. Implementation of AuditorAware based on Spring Security
class SpringSecurityAuditorAware implements AuditorAware<User> {

  public Optional<User> getCurrentAuditor() {

    return Optional.ofNullable(SecurityContextHolder.getContext())

The implementation accesses the Authentication object provided by Spring Security and looks up the custom UserDetails instance that you have created in your UserDetailsService implementation. We assume here that you are exposing the domain user through the UserDetails implementation but that, based on the Authentication found, you could also look it up from anywhere. :leveloffset: -1

9. Spring Data Neo4j Reference Documentation

9.1. Introduction

It is important to understand how a Spring Data Neo4j (SDN) application is structured because this could have implications in how you design your application.

9.1.1. SDN Architecture

A high level look of the architecture looks like:

Spring Data Neo4j Architecture
  • Drivers are used to connect to the database. At the moment these come in three variants: Embedded, HTTP and the binary protocol Bolt. The latter uses the official Neo4j Java driver.

  • Neo4j Object Graph Mapper (Neo4j-OGM)

  • Spring Data Neo4j provides code on top of Neo4-OGM to help quickly build Spring based Neo4j apps.

Those coming from other Spring Data projects or are familiar with ORM products like JPA or Hibernate may quickly recognise this architecture.

Please read the Migration Guide for a smooth upgrade from Spring Data Neo4j 3.

9.1.2. How to use this reference

Spring Data Neo4j is largely broken up into two main components:

It is recommended SDN developers also familiarise themselves with Neo4j-OGM. The Neo4j-OGM reference documentation has been reproduced after this section for convenience.

9.2. Getting started

Depending on what type of project you are doing there are several options when it comes to creating a new SDN project:

If you plan on using Neo4j in server mode, you will also need a running instance. Refer to the Getting Started section of the Neo4j Developer manual on how to get that up and running.

9.2.1. Using Spring Boot

To create a Spring Boot project simply go to https://start.spring.io and specify a group and artifact like: org.spring.neo4j.example and demo. In the Dependencies box type: "Neo4j". You can also add any other Spring support like "Web" etc. Once you are satisfied with your dependencies hit the generate button, download the zip and unzip into your workspace.

9.2.2. Using Spring Tool Suite

To create a Spring project in STS go to File → New → Spring Template Project → Simple Spring Utility Project → press Yes when prompted. Then enter a project and a package name such as org.spring.neo4j.example.

Then add the following to pom.xml dependencies section.


  <!-- other dependency elements omitted -->



Also change the version of Spring in the pom.xml to be


9.2.3. Using Dependency Management

Spring Data Neo4j projects can be built using Maven, Gradle or any other tool that supports Maven’s repository system.

Adding the depedency-management-block is not necessary in a Spring Boot based project. Spring Boot manages Spring Data dependencies and releasetrains automatically.

By default, SDN will use the Bolt driver to connect to Neo4j and you don’t need to declare it as a separate dependency in your pom.xml. If you want to use the embedded or HTTP drivers in your production application, you must add the following dependencies as well.



    <!-- add this dependency if you want to use the embedded driver -->

    <!-- add this dependency if you want to use the HTTP driver -->
Maven dependencies for testing
Spring Boot brings spring-test through spring-boot-starter-test, which simplifies testing a lot. You don’t need to declare spring-test explicitly.

Using neo4j-harness brings in a dependency on Jetty container. If you use Spring Boot dependency management the version may be set to an incompatible version. This may be avoided by overriding jetty.version property to a version required by neo4j server.

    <!-- version compatible with neo4j 3.3.0 -->

Also having the jetty dependency on the classpath might cause your application to use jetty as a servlet container in your tests instead of defaulting to Tomcat. You can avoid that e.g. by forcing the EmbeddedTomcat auto-configuration.

// Import tomcat autoconfig to avoid starting Jetty, which is on classpath because of neo4j dependencies

Gradle dependencies are basically the same as Maven:

dependencies {
    compile 'org.springframework.data:spring-data-neo4j:{version}'

    // add this dependency if you want to use the embedded driver
    compile 'org.neo4j:neo4j-ogm-embedded-driver:{ogm-version}'

    // add this dependency if you want to use the Http driver
    compile 'org.neo4j:neo4j-ogm-http-driver:{ogm-version}'


9.2.4. Examples

There is a github repository with several examples that you can download and play around with to get a feel for how the library works.

9.2.5. Configuration

For those not familiar with how to configure the Spring container using Java based bean metadata instead of XML based metadata see the high-level introduction in the reference docs here as well as the detailed documentation here.

For most applications the following configuration is all that’s needed to get up and running.

Spring Data Neo4j repositories using JavaConfig
@EnableNeo4jRepositories(basePackages = "org.neo4j.example.repository")
public class MyConfiguration {

    public SessionFactory sessionFactory() {
        // with domain entity base package(s)
        return new SessionFactory(configuration(), "org.neo4j.example.domain");

    public org.neo4j.ogm.config.Configuration configuration() {
        ConfigurationSource properties = new ClasspathConfigurationSource("ogm.properties");
        org.neo4j.ogm.config.Configuration configuration = new org.neo4j.ogm.config.Configuration.Builder(properties).build();
        return configuration;

    public Neo4jTransactionManager transactionManager() {
        return new Neo4jTransactionManager(sessionFactory());


Here we wire up a SessionFactory configured from defaults. We can change these defaults by providing an ogm.properties file at the root of the classpath or by passing in a org.neo4j.ogm.config.Configuration object. The last infrastructure component declared here is the Neo4jTransactionManager. We finally activate Spring Data Neo4j repositories using the @EnableNeo4jRepositories annotation. If no base package is configured it will use the one the configuration class resides in.

Note that you will have to activate @EnableTransactionManagement explicitly to get annotation based configuration at facades working as well as define an instance of this Neo4jTransactionManager with the bean name transactionManager. The example above assumes you are using component scanning.

To allow your query methods to be transactional simply use @Transactional at the repository interface you define.

Driver Configuration

SDN provides support for connecting to Neo4j using different drivers.

The following drivers are available.

  • Http driver

  • Embedded driver

  • Bolt driver

To configure the driver programmatically, create a Neo4j-OGM Configuration bean and pass it as the first argument to the SessionFactory constructor in your Spring configuration:

Java Configuration
public org.neo4j.ogm.config.Configuration configuration() {
    org.neo4j.ogm.config.Configuration configuration = new org.neo4j.ogm.config.Configuration.Builder()
            .credentials("user", "secret")
    return configuration;

public SessionFactory sessionFactory() {
    return new SessionFactory(configuration(), <packages> ); (1)
1 packages is a list of Java packages containing the annotated domain model.

Configuration can also be initialized from an external file like this.

public org.neo4j.ogm.config.Configuration configuration() {
    ConfigurationSource properties = new ClasspathConfigurationSource("db.properties");
    return new org.neo4j.ogm.config.Configuration.Builder(properties).build();

where db.properties looks like

connection.pool.size=... #see Java driver doc
encryption.level=... #see Java driver doc
trust.strategy=... #see Java driver doc
trust.certificate.file=... #see Java driver doc
connection.liveness.check.timeout=... #see Java driver doc
verify.connection=... #see Java driver doc
The driver is automatically inferred from the URI scheme.
To set up authentication, TLS or other advanced options please see the Configuration section of the Neo4j-OGM Reference.
As of 4.2.0 the Neo4j-OGM embedded driver no longer ships with the Neo4j kernel. Users are expected to provide this dependency through their dependency management system.
Spring Boot Applications

Spring Boot 2.0 works straight out of the box with Spring Data Neo4j 5.

Update your Spring Boot Maven POM with the following. You may need to add <repositories> depending on versioning (when using milestone or snapshot versions).


Then add to your Spring Boot configuration class these annotations:

@EntityScan(basePackages = "com.company.project.domain")
Configuring Events with Boot

When defining a Spring EventListener. Simply defining a @Bean will automatically register it with the SessionFactory.

9.2.6. Connecting to Neo4j

The SessionFactory is needed by SDN to create instances of org.neo4j.ogm.session.Session as required. When constructed, it sets up the object-graph mapping metadata, which is then used across all Session objects that it creates. As seen in the above example, the packages to scan for domain object metadata should be provided to the SessionFactory constructor.

Your application typically connects only to one instance of Neo4j. Therefore there is usually only one SessionFactory per application. This SessionFactory should be configured in such a way that it scans all necessary packages. @EnableNeo4jRepositories detects one single bean of type SessionFactory out of the box and you don’t need to configure anything more.

In cases however where your setup requires the application to connect to multiple different instances of Neo4j, SDN allows you to specify that instance in @EnableNeo4jRepositories as follows:

    basePackages = "org.neo4j.example.repository",
    sessionFactoryRef = "mySpecialSessionFactory" (1)
public class MyConfiguration {
1 Use the name of the session factory you want to be bound to the repositories for that package

In cases like this SDN also supports multiple declarations of @EnableNeo4jRepositories that target different packages. Our recommendation however is connecting one application to one instance. If your domains are so different that they are stored in different databases, a microservices approach might be a better fit to your application.

9.3. Neo4j-OGM Support

To get started, you need only your domain model and the annotations provided by the Neo4j-OGM library. You use annotations to mark domain objects to be reflected by nodes and relationships of the graph database. Annotations for individual fields allow you to declare how fields should be processed and mapped to properties of nodes in the graph.

Refer to the Neo4j-OGM documentation for more details.

9.3.1. What is Neo4j-OGM?

An OGM (Object Graph Mapper) maps nodes and relationships in the graph to objects and references in your domain model. Object instances are mapped to nodes while object references are mapped using relationships, or serialized to properties. JVM primitives are mapped to properties of a node or a relationship. An OGM lets you create a view of your database based on your domain model. It also provides the flexibility to supply custom queries in cases where the queries generated by Neo4j-OGM are insufficient.

The OGM can be thought of as analogous to Hibernate or JPA. Users should have an understanding of what an object mapper does when using this guide.

While SDN’s repositories will cover a majority of user scenarios, sometimes they don’t offer enough options. Neo4j-OGM’s Session offers a convenient API to interact more direct with a Neo4j graph database. SDN now allows you to wire up the Neo4j-OGM Session directly into your Spring managed beans.

Understanding the Session

A Session is used to drive the object-graph mapping framework. All repository implementations are backed by the Session. It keeps track of the changes that have been made to entities and their relationships. The reason it does this is so that only entities and relationships that have changed get persisted on save, which is particularly efficient when working with large graphs.

Sessions are usually bound to a thread by default and rely on the garbage collector to clean them up once they are out of scope of processing. For most users this means there is nothing to configure. Request/response type applications SDN will take care of session management for you (as defined in the configuration section above). If you have a batch or long running desktop type application you may want to know how you can control using the session a bit more.

Design Consideration: Session caching

Once an entity is tracked by the session, reloading this entity within the scope of the same session will result in the session cache returning the previously loaded entity. However, the subgraph in the session will expand if the entity or its related entities retrieve additional relationships from the graph.

If you want to fetch fresh data from the graph, then this can be achieved by using a new session or clearing the current sessions context using org.neo4j.ogm.session.Session.clear().

The lifetime of the Session can be managed in code. For example, associated with single fetch-update-save cycle or unit of work.

If your application relies on long-running sessions then you may not see changes made from other users and find yourself working with outdated objects. On the other hand, if your sessions have too narrow a scope then your save operations can be unnecessarily expensive, as updates will be made to all objects if the session isn’t aware of the those that were originally loaded.

There’s therefore a trade off between the two approaches. In general, the scope of a Session should correspond to a "unit of work" in your application.

9.3.2. Basic Operations

For Spring Data Neo4j, low level operations are handled by Neo4j-OGM Session. Basic operations are limited to CRUD operations on entities and executing arbitrary Cypher queries; more low-level manipulation of the graph database is not possible.

Given that the latest version of the framework is driven by Cypher queries alone, there’s no way to work directly with Node and Relationship objects, especially in remote server mode. Similarly, the traverse() method has disappeared, again because the underlying query-driven model doesn’t handle it in an efficient way.

If you did rely on low-level manipulation of the graph database itself or being able to use traverse() in previous versions of Spring Data Neo4j, then your best options are:

  1. Write a Cypher query to perform the operations on the nodes/relationships instead

  2. Write a Neo4j server extension and call it over REST from your application

Of course, there are pros and cons to both of these approaches, but these are largely outside the scope of this document. In general, for low-level, very high-performance operations like complex graph traversals you will get the best performance by writing a server-side extension. For most purposes, though, Cypher will be performant and expressive enough to perform the operations that you need.

9.3.3. Entity Persistence

Session allows you to save, load, loadAll and delete entities. The eagerness with which objects are retrieved is controlled by specifying the 'depth' argument to any of the load methods.

All of these basic CRUD methods just call onto the underlying methods of Session, albeit with transaction handling and exception translation managed for you by SDN’s TransactionManager bean.

9.3.4. Cypher Queries

The Session also allows execution of arbitrary Cypher queries via its query, queryForObject and queryForObjects methods. Cypher queries that return tabular results should be passed into the query method. An org.neo4j.ogm.session.result.Result is returned. This consists of org.neo4j.ogm.session.result.QueryStatistics representing statistics of modifying cypher statements if applicable, and an Iterable<Map<String,Object>> containing the raw data, of which nodes and relationships are mapped to domain entities if possible. The keys in each Map correspond to the names listed in the return clause of the executed Cypher query.

Modifications made to the graph via Cypher queries directly will not be reflected in your domain objects within the session.

9.3.5. Transactions

If you configured the Neo4jTransactionManager bean, any Session that is managed by Spring will automatically take part in thread contextual transactions. In order to do this you will need to wrap your service code using @Transactional or the TransactionTemplate.

It is important to know that if you enable Transactions ALL code that uses the Session directly must be enclosed in a @Transactional annotation. Declarative Spring Data repositories (see Neo4j Repositories) are already marked as @Transactional and will create implicit transactions if no transaction boundaries are defined at the callers site.

For more details see Transactions

9.4. Neo4j Repositories

9.4.1. Introduction

This chapter will point out the features for repository support for Neo4j and the Neo4j-OGM. This builds on the core repository support explained in Working with Spring Data Repositories. So make sure you have got a sound understanding of the basic concepts explained there.

The following table outlines the repositories functionality currently either supported, partially supported or not supported in SDN:

Feature Supported in SDN Notes

CrudRepository support

PagingAndSortingRepository support

Derived Count Queries

JavaConfig annotation based configuration

XML based configuration

Multi Spring Data module support

Configurable Query Lookup Strategy

Derived Query support

See supported keywords for query methods below

Derived Query Property expressions support

Paging and Slice support

Derived query paging limit support

Java 8 Streaming and Optional support

@Async support

Custom behaviour on repositories

QueryDslPredicateExecutor support

Web support (incl. Spring Data REST)

Partial: QueryDSL not supported.

Repository populators

9.4.2. Usage

The Repository instances are created automatically through Spring and can be autowired into your Spring beans as required. You don’t have to provide an implementation for the interfaces you declared.

Using basic Neo4jRepository CRUD-methods
public interface PersonRepository extends Neo4jRepository<Person, Long> {}

public class MySpringBean {

   private final PersonRepository repo;

   public MySpringBean(PersonRepository repo) {
    this.repo = repo;

// then you can use the repository as you would any other object
Person michael = repo.save(new Person("Michael", 36));

Optional<Person> dave = repo.findById(123);

long numberOfPeople = repo.count();

The recommended way of providing repositories is to define a repository interface per aggregate root and not for every domain class. The underlying Spring repository infrastructure will automatically detect these repositories, along with additional implementation classes, and create an injectable repository implementation to be used in services or other Spring beans.

The repositories provided by Spring Data Neo4j build on the composable repository infrastructure in Spring Data Commons. These allow for interface-based composition of repositories consisting of provided default implementations for certain interfaces and additional custom implementations for other methods.

Spring Data Neo4j comes with a single org.springframework.data.repository.PagingAndSortingRepository specialisation called Neo4jRepository<T. ID> used for all object-graph mapping repositories. This sub-interface also adds specific finder methods that take a depth argument to control the horizon with which related entities are fetched and saved. Generally, it provides all the desired repository methods. If other operations are required then the additional repository interfaces should be added to the individual interface declaration.

9.4.3. Query Methods

Query and Finder Methods

Most of the data access operations you usually trigger on a repository will result in a query being executed against the Neo4j database. Defining such a query is just a matter of declaring a method on the repository interface.

Example 57. PersonRepository with query methods
public interface PersonRepository extends PagingAndSortingRepository<Person, String> {

    List<Person> findByLastname(String lastname);                      (1)

    Page<Person> findByFirstname(String firstname, Pageable pageable); (2)

    Person findByShippingAddresses(Address address);                   (3)

    Stream<Person> findAllBy();                                        (4)
1 The method shows a query for all people with the given last name. The query will be derived parsing the method name for constraints which can be concatenated with And and Or. Thus the method name will result in a query expression of {"lastname" : lastname}.
2 Applies pagination to a query. Just equip your method signature with a Pageable parameter and let the method return a Page instance and we will automatically page the query accordingly.
3 Shows that you can query based on properties which are not a primitive type.
4 Uses a Java 8 Stream which reads and converts individual elements while iterating the stream.
Table 2. Supported keywords for query methods
Keyword Sample Cypher snippet


findByLaunchDateAfter(Date date)

n.launchDate > date


findByLaunchDateBefore(Date date)

n.launchDate < date

Containing (String)

findByNameContaining(String namePart)

n.name CONTAINS namePart

Containing (Collection)

findByEmailAddressesContains(Collection<String> addresses)

findByEmailAddressesContains(String address)

ANY(collectionFields IN [addresses] WHERE collectionFields in n.emailAddresses)

ANY(collectionFields IN address WHERE collectionFields in n.emailAddresses)


findByNameIn(Iterable<String> names)

n.name IN names


findByScoreBetween(double min, double max)
findByScoreBetween(Range<Double> range)

n.score >= min AND n.score <= max
Depending on the Range definition n.score >= min AND n.score <= max or n.score > min AND n.score < max


findByNameStartingWith(String nameStart)

n.name STARTS WITH nameStart


findByNameEndingWith(String nameEnd)

n.name ENDS WITH nameEnd






n.activated = true



NOT(n.activated = true)


findByNameIs(String name)

n.name = name



NOT(n.name IS NULL)



n.name IS NULL


findByScoreGreaterThan(double score)

n.score > score


findByScoreGreaterThanEqual(double score)

n.score >= score


findByScoreLessThan(double score)

n.score < score


findByScoreLessThanEqual(double score)

n.score <= score


findByNameLike(String name)

n.name =~ name


findByNameNotLike(String name)

NOT(n.name =~ name)


findByLocationNear(Distance distance, Point point)

distance( point(n),point({latitude:lat, longitude:lon}) ) < distance


findByNameRegex(String regex)

n.name =~ regex


findByNameAndDescription(String name, String description)

n.name = name AND n.description = description


findByNameOrDescription(String name, String description)

n.name = name OR n.description = description (Cannot be used to OR nested properties)

Annotated queries

Queries using the Cypher graph query language can be supplied with the @Query annotation.

That means a repository method annotated with
@Query("MATCH (:Actor {name:$name})-[:ACTED_IN]->(m:Movie) return m")
will use the supplied query to retrieve data from Neo4j.

The named or indexed parameter $param will be substituted by the actual method parameter. Node and relationship entities are handled directly and converted into their respective ids. All other parameters types are provided directly (i.e. String, Long, etc.).

There is special support for the Pageable parameter from Spring Data Commons, which is supported to add programmatic paging and slicing (alternatively static paging and sorting can be supplied in the query string itself).

If it is required that paged results return the correct total count, the @Query annotation can be supplied with a count query in the countQuery attribute. This query is executed separately after the result query and its result is used to populate the number of elements on the page.

Custom queries do not support a custom depth. Additionally, @Query does not support mapping a path to domain entities, as such, a path should not be returned from a Cypher query. Instead, return nodes and relationships to have them mapped to domain entities.

Named queries

Sometimes it makes sense to extract e.g. a long query. Spring Data Neo4j will look in the META-INF/neo4j-named-queries.properties file to find named queries. If you provide a query property like User.findByQuery=MATCH (e) WHERE e.name=$name RETURN e you can refer to this method by providing a finder method in your repository. The repository has to support the given entity type (in this example User) and the method has to be named as the defined one (findByQuery). As you can see in the example it is possible to parameterize the query. Named count query can be specified by adding .countQuery suffix to the related query property key. For example, if the next query should return paged result User.findAllByQuery=MATCH (e) RETURN e, the count query can be specified by the following way: User.findAllByQuery.countQuery=MATCH (e) RETURN count(e).

Query results

Typical results for queries are Iterable<Type>, Iterable<Map<String,Object>> or simply Type. Nodes and relationships are converted to their respective entities (if they exist). Other values are converted using the registered conversion services (e.g. enums).

Cypher examples
MATCH (n) WHERE id(n)=9 RETURN n

returns the node with id 9

MATCH (movie:Movie {title:'Matrix'}) RETURN movie

returns the nodes which are indexed with title equal to 'Matrix'

MATCH (movie:Movie {title:'Matrix'})←[:ACTS_IN]-(actor) RETURN actor.name

returns the names of the actors that have a ACTS_IN relationship to the movie node for 'Matrix'

MATCH (movie:Movie {title:'Matrix'})←[r:RATED]-(user) WHERE r.stars > 3 RETURN user.name, r.stars, r.comment

returns users names and their ratings (>3) of the movie titled 'Matrix'

MATCH (user:User {name='Michael'})-[:FRIEND]-(friend)-[r:RATED]->(movie) RETURN movie.title, AVG(r.stars), COUNT(*) ORDER BY AVG(r.stars) DESC, COUNT(*) DESC

returns the movies rated by the friends of the user 'Michael', aggregated by movie.title, with averaged ratings and rating-counts sorted by both

Examples of Cypher queries placed on repository methods with @Query where values are replaced with method parameters, as described in the Annotated queries) section.

public interface MovieRepository extends Neo4jRepository<Movie, Long> {

    // returns the node with id equal to idOfMovie parameter
    @Query("MATCH (n) WHERE id(n)=$0 RETURN n")
    Movie getMovieFromId(Integer idOfMovie);

    // returns the nodes which have a title according to the movieTitle parameter
    @Query("MATCH (movie:Movie {title=$0}) RETURN movie")
    Movie getMovieFromTitle(String movieTitle);

    // same with optional result
    @Query("MATCH (movie:Movie {title=$0}) RETURN movie")
    Optional<Movie> getMovieFromTitle(String movieTitle);

    // returns a Page of Actors that have a ACTS_IN relationship to the movie node with the title equal to movieTitle parameter.
    @Query(value = "MATCH (movie:Movie {title=$0})<-[:ACTS_IN]-(actor) RETURN actor", countQuery= "MATCH (movie:Movie {title=$0})<-[:ACTS_IN]-(actor) RETURN count(actor)")
    Page<Actor> getActorsThatActInMovieFromTitle(String movieTitle, PageRequest page);

    // returns a Page of Actors that have a ACTS_IN relationship to the movie node with the title equal to movieTitle parameter with an accurate total count
    @Query(value = "MATCH (movie:Movie {title=$0})<-[:ACTS_IN]-(actor) RETURN actor", countQuery = "MATCH (movie:Movie {title=$0})<-[:ACTS_IN]-(actor) RETURN count(*)")
    Page<Actor> getActorsThatActInMovieFromTitle(String movieTitle, Pageable page);

    // returns a Slice of Actors that have a ACTS_IN relationship to the movie node with the title equal to movieTitle parameter.
    @Query("MATCH (movie:Movie {title=$0})<-[:ACTS_IN]-(actor) RETURN actor")
    Slice<Actor> getActorsThatActInMovieFromTitle(String movieTitle, Pageable page);

    // returns users who rated a movie (movie parameter) higher than rating (rating parameter)
    @Query("MATCH (movie:Movie)<-[r:RATED]-(user) " +
           "WHERE id(movie)=$movieId AND r.stars > {rating} " +
           "RETURN user")
    Iterable<User> getUsersWhoRatedMovieFromTitle(@Param("movieId") Movie movie, @Param("rating") Integer rating);

    // returns users who rated a movie based on movie title (movieTitle parameter) higher than rating (rating parameter)
    @Query("MATCH (movie:Movie {title:$0})<-[r:RATED]-(user) " +
           "WHERE r.stars > $1 " +
           "RETURN user")
    Iterable<User> getUsersWhoRatedMovieFromTitle(String movieTitle, Integer rating);

    @Query(value = "MATCH (movie:Movie) RETURN movie;")
    Stream<Movie> getAllMovies();
Queries derived from finder-method names

Using the metadata infrastructure in the underlying object-graph mapper, a finder method name can be split into its semantic parts and converted into a cypher query. Navigation along relationships will be reflected in the generated MATCH clause and properties with operators will end up as expressions in the WHERE clause. The parameters will be used in the order they appear in the method signature so they should align with the expressions stated in the method name.

Some examples of methods of a PersonRepository and the Cypher queries derived from them
public interface PersonRepository extends Neo4jRepository<Person, Long> {

    // MATCH (person:Person {name=$0}) RETURN person
    Person findByName(String name);

    // MATCH (person:Person)
    // WHERE person.age = $0 AND person.married = $1
    // RETURN person
    Iterable<Person> findByAgeAndMarried(int age, boolean married);

    // MATCH (person:Person)
    // WHERE person.age = $0
    // RETURN person ORDER BY person.name SKIP $skip LIMIT $limit
    Page<Person> findByAge(int age, Pageable pageable);

    // MATCH (person:Person)
    // WHERE person.age = $0
    // RETURN person ORDER BY person.name
    List<Person> findByAge(int age, Sort sort);

    // Allow a custom depth as a parameter
    Person findByName(String name, @Depth int depth);

    // Set a fix depth of 0 for the query
    @Depth(value = 0)
    Person findBySurname(String surname);

Mapping Query Results

For queries executed via @Query repository methods, it’s possible to specify a conversion of complex query results to POJOs. These result objects are then populated with the query result data. Those POJOs are easier to handle and might be used as Data Transfer Objects (DTOs) as they are not attached to a Session and don’t participate in any lifecycle. To take advantage of this feature, use a class annotated with @QueryResult as the method return type.

The properties of your @QueryResult annotated class must have the same names as the returned values. Please keep in mind that Java and Cypher are case-sensitive.

Example of query result mapping
public interface MovieRepository extends Neo4jRepository<Movie, Long> {

    @Query("MATCH (movie:Movie)-[r:RATING]->(), (movie)<-[:ACTS_IN]-(actor:Actor) " +
           "WHERE movie.id=$0 " +
           "RETURN movie as movie, COLLECT(actor) AS cast, AVG(r.stars) AS averageRating")
    MovieData getMovieData(String movieId);

public class MovieData {
    Movie movie;
    Double averageRating;
    Set<Actor> cast;
Sorting and Paging

Spring Data Neo4j supports sorting and paging of results when using Spring Data’s Pageable and Sort interfaces.

Repository-based paging
Pageable pageable = PageRequest.of(0, 3);
Page<World> page = worldRepository.findAll(pageable, 0);
Repository-based sorting
Sort sort = new Sort(Sort.Direction.ASC, "name");
Iterable<World> worlds = worldRepository.findAll(sort, 0)) {
Repository-based sorting with paging
Pageable pageable = PageRequest.of(0, 3, Sort.Direction.ASC, "name");
Page<World> page = worldRepository.findAll(pageable, 0);

Spring Data Repositories usually return the domain model (either as @NodeEntity or as a @QueryResult) when using query methods. However, sometimes you may need a different view of that model for various reasons. In this section you will learn how to define projections to serve up simplified and reduced views of resources.

Look at the following domain model:

public class Cinema {

  private Long id;
  private String name, location;

  @Relationship(type = "VISITED", direction = Relationship.INCOMING)
  private Set<User> visited = new HashSet<>();

  @Relationship(type = "BLOCKBUSTER", direction = Relationship.OUTGOING)
  private Movie blockbusterOfTheWeek;

  // …

This Cinema has several attributes:

  • id is the graph id

  • name and location are data attributes

  • visited and blockbusterOfTheWeek are links to other domain objects

Now assume we create a corresponding repository as follows:

public interface CinemaRepository extends Neo4jRepository<Cinema, Long> {

  Cinema findByName(String name);

Spring Data will return the domain object including all of its attributes and all the users that visited this cinema. That can be a big amount of data and can lead to performance issues.

There are several ways to avoid that :

Example 58. Simple Projection
public interface CinemaNameAndBlockbuster {  (1)

	String getName(); (2)
	Movie getBlockbusterOfTheWeek();

This projection has the following details:

1 A plain Java interface making it declarative.
2 Only some attributes of the entity are exported.

The CinemaNameAndBlockbuster projection only has getters for name and blockbusterOfTheWeek meaning that it will not serve up any user information. The query method definition returns in this case CinemaNameAndBlockbuster instead of Cinema.

interface CinemaRepository extends Neo4jRepository<Cinema, Long> {

  CinemaNameAndBlockbuster findByName(String name);

Projections declare a contract between the underlying type and the method signatures related to the exposed properties. Hence it is required to name getter methods according to the property name of the underlying type. If the underlying property is named name, then the getter method must be named getName otherwise Spring Data is not able to look up the source property. This type of projection is also called closed projection.

Closed projections expose a subset of properties that could be used to optimize the query in a way that reduces the selected fields from the data store. However, it is not implemented at the moment. For performance sensitive querying, you can still use custom queries with maps or QueryResult (see Mapping Query Results)

The other type is, as you might imagine, an open projection.

Remodelling data

So far, you have seen how projections can be used to reduce the information that is presented to the user. Projections can be used to adjust the exposed data model. You can add virtual properties to your projection. Look at the following projection interface:

Example 59. Renaming a property
interface RenamedProperty {                 (1)

  String getCinemaName();                   (2)

  String getBlockbusterOfTheWeekName();     (3)

This projection has the following details:

1 A plain Java interface making it declarative.
2 Expose the name attribute as a virtual property called cinemaName.
3 Export the name sub-property of the linked Movie entity as a virtual property.

The backing domain model does not have these properties so we need to tell Spring Data from where they are obtained. Virtual properties are the place where @Value comes into play. The cinemaName getter is annotated with @Value to use SpEL expressions pointing to the backing property name. You may have noticed name is prefixed with target which is the variable name pointing to the backing object. Using @Value on methods allows defining where and how the value is obtained.

@Value gives full access to the target object and its nested properties. SpEL expressions are extremely powerful as the definition is always applied to the projection method.

We could imagine this:

interface RenamedProperty {

  @Value("#{target.name} #{(target.location == null) ? '' : target.location}")
  String getNameAndLocation();

In this example, the location is appended to the cinema name only if it is available.

9.4.4. Transactions

Neo4j is a transactional database, only allowing operations to be performed within transaction boundaries. Spring Data Neo4j integrates nicely with both the declarative transaction support with @Transactional as well as the manual transaction handling with TransactionTemplate.

The methods on the repositories instances are transactional by default. If you are, for example, simply just looking up an object through a repository then you do not need to define anything else: SDN will take of everything for you. That said, it is strongly recommended that you always annotate any service boundaries to the database with a @Transactional annotation. This way all your code for that method will always run in one transaction, even if you add a write operation later on.

More standard behaviour with transactions is using a facade or service implementation that typically covers more than one repository or database call as part of a 'Unit of Work'. Its purpose is to define transactional boundaries for non-CRUD operations:

SDN only supports PROPAGATION_REQUIRED and ISOLATION_DEFAULT type transactions.
Using an @Service as facade to define transaction boundaries for multiple repository calls
class UserManagementImpl implements UserManagement {

  private final UserRepository userRepository;
  private final RoleRepository roleRepository;

  public UserManagementImpl(UserRepository userRepository,
    RoleRepository roleRepository) {
    this.userRepository = userRepository;
    this.roleRepository = roleRepository;

  public void addRoleToAllUsers(String roleName) {

    Role role = roleRepository.findByName(roleName);

    for (User user : userRepository.findAll()) {

This will cause all calls to addRoleToAllUsers(…) to run inside a transaction (participating in an existing one or create a new one if none already running). The transaction configuration at the repositories will be neglected as the outer transaction configuration determines the actual one used.

It is highly recommended that users understand how Spring transactions work. Below are some excellent resources:

Read only Transactions

You can start a read only transaction by marking a class or method with @Transactional(readOnly=true).

Be careful when nesting transactions. Spring’s @Transactional propagates by default outer transactions and doesn’t validate whether they are compatible with inner. The Neo4jTransactionManager can be configured to validate existing transaction by calling #setValidateExistingTransaction(true) during bean initialization. For more details see Spring’s documentation.
Transaction Bound Events

SDN provides the ability to bind the listener of an event to a phase of the transaction. The typical example is to handle the event when the transaction has completed successfully: this allows events to be used with more flexibility when the outcome of the current transaction actually matters to the listener.

The transaction module implements an EventListenerFactory that looks for the new @TransactionalEventListener annotation. When this one is present, an extended event listener that is aware of the transaction is registered instead of the default.

Example: An order creation listener.
public class MyComponent {

  @TransactionalEventListener(condition = "#creationEvent.awesome")
  public void handleOrderCreatedEvent(CreationEvent<Order> creationEvent) {


@TransactionalEventListener is a regular @EventListener and also exposes a TransactionPhase, the default being AFTER_COMMIT. You can also hook other phases of the transaction (BEFORE_COMMIT, AFTER_ROLLBACK and AFTER_COMPLETION that is just an alias for AFTER_COMMIT and AFTER_ROLLBACK).

By default, if no transaction is running the event isn’t sent at all as we can’t obviously honor the requested phase, but there is a fallbackExecution attribute in @TransactionalEventListener that tells Spring to invoke the listener immediately if there is no transaction.

Only public methods in a managed bean can be annotated with @EventListener to consume events. @TransactionalEventListener is the annotation that provides transaction-bound event support described here.

To find out more about Spring’s Event listening capabilities see the Spring reference manual and How to build Transaction aware Eventing with Spring 4.2.

9.4.5. Clustering support

Bookmark management

Neo4j causal clusters use bookmarks to manage read your own writes scenarios. You’ll find background information on the way causal clusters work in the Neo4j operations manual.

In SDN, you can use the bookmark management feature to handle these scenarios easily. You just need to:

  • Add the @EnableBookmarkManagement annotation once on one of your Spring configuration classes.

  • Provide one bean implementing org.springframework.data.neo4j.bookmark.BookmarkManager. SDN supplies an implementation named CaffeineBookmarkManager based on the popular caching framework Caffeine.

  • Add @UseBookmark to each transactional Java method involved in a read your own writes scenario.

A configuration using Caffeine may look like this:

public class ExampleConfiguration {

    public BookmarkManager bookmarkManager() {
        return new CaffeineBookmarkManager();

Please make sure that Caffeine is on the class path before you use this configuration.

Every method annotated with @UseBookmark will then collect the bookmarks coming from the database at the end of transactions. These bookmarks are then stored into a SDN managed context, and reused on later calls to other @UseBookmark annotated methods.

@UseBookmark has to be used on @Transactional annotated methods.

9.4.6. Miscellaneous

CDI integration

Instances of the repository interfaces are usually created by a container and Spring is the most natural choice when working with Spring Data. There’s sophisticated support to easily set up Spring to create bean instances documented in Creating Repository Instances. Spring Data Neo4j ships with a custom CDI extension that allows using the repository abstraction in CDI environments.

You can now set up the infrastructure by implementing a CDI Producer for the SessionFactory and Session:

class SessionFactoryProducer {

  public SessionFactory createSessionFactory() {
    return new SessionFactory("package");

  public void close(@Disposes SessionFactory sessionFactory) {

The necessary setup can vary depending on the JavaEE environment you run in. It might also just be enough to redeclare a Session as CDI bean as follows:

class CdiConfig {

  public Session session;

In this example, the container has to be capable of creating Neo4j-OGM Sessions itself. All the configuration does is re-exporting the Neo4j-OGM Session as CDI bean.

The Spring Data Neo4j CDI extension will pick up all sessions available as CDI beans and create a proxy for a Spring Data repository whenever a bean of a repository type is requested by the container. Thus obtaining an instance of a Spring Data repository is a matter of declaring an @Injected property:

class RepositoryClient {

  PersonRepository repository;

  public void businessMethod() {
    List<Person> people = repository.findAll();
JSR-303 (Bean Validation) Support

Spring Data Neo4j allows developers to use JSR-303 annotations like @NotNull etc. on their domain models. While this is supported, it’s not a best practice. It is highly recommended to create JSR-303 annotations on actual Java Beans, similar to things like Data Transfer Objects (DTOs).

Conversion Service

It is possible to have Spring Data Neo4j use converters registered with Spring’s ConversionService. There must be one unique instance of a ConversionService-Bean in your application context to use this. If there is more than one instance, you have to mark the one to be used by SDN with @Primary, otherwise an internal conversion service will be used.

When those requirements are met, use the graphPropertyType attribute on the @Convert annotation instead of specifying an org.neo4j.ogm.typeconversion.AttributeConverter through its value:

Using graphPropertyType
public class MyEntity {

    @Convert(graphPropertyType = Integer.class)
    private DecimalCurrencyAmount fundValue;


Spring Data Neo4j will look for converters registered with Spring’s ConversionService that can convert both to and from the type specified by graphPropertyType and use them if they exist.

Default converters and those defined explicitly via an implementation of org.neo4j.ogm.typeconversion.AttributeConverter will take precedence over converters registered with Spring’s ConversionService.

Neo4jRepository<T, ID> should be the interface from which your entity repository interfaces inherit, with T being specified as the domain entity type to persist. ID is defined by the field type annotated with @Id.

Examples of methods you get for free out of Neo4jRepository are as follows. For all of these examples the ID parameter is a Long that matches the graph id:

Load an entity instance via an id

Optional<T> findById(id)

Check for existence of an id in the graph

boolean existsById(id)

Iterate over all nodes of a node entity type

Iterable<T> findAll() Iterable<T> findAll(Sort …​) Page<T> findAll(Pageable …​)

Count the instances of the repository entity type

Long count()

Save entities

T save(T) and Iterable<T> saveAll(Iterable<T>)

Delete graph entities

void delete(T), void deleteAll(Iterable<T>), and void deleteAll()

For users coming from versions before 4.2.x, Neo4jRepository has replaced GraphRepository but essentially has the same features.

Spring Data Neo4j integrates into the Spring Data auditing infrastructure to keep track of who created or changed an entity and the point in time this happened.

While Spring Data Neo4j uses the same annotations for auditing as all Spring Data modules do, auditing support itself has to be explicitly enabled. To enable Spring Data Neo4j’s auditing, use @EnableNeo4jAuditing on a @Configuration-class as shown in Neo4jConfiguration.java.

import org.springframework.data.neo4j.annotation.EnableNeo4jAuditing;

public class Neo4jConfiguration {}
If you are working with custom ids by setting them directly or using your own IdStrategy, the auditing support is limited. It it is not possible for Spring Data Neo4j to figure out if an entity is new or already exists in the database. As a consequence the fields annotated with @CreatedBy and @CreatedDate will never get filled.

Please refer to the auditing section of the shared Spring Data reference for further details.

10. Neo4j-OGM Reference Documentation

This chapter is taken from the Official Neo4j-OGM Reference Documentation.

10.1. Introduction

Neo4j-OGM is a fast object-graph mapping library for Neo4j, optimised for server-based installations utilising Cypher.

It aims to simplify development with the Neo4j graph database and like JPA, it uses annotations on simple POJO domain objects to do so.

With a focus on performance, Neo4j-OGM introduces a number of innovations, including:

  • non-reflection based classpath scanning for much faster startup times

  • variable-depth persistence to allow you to fine-tune requests according to the characteristics of your graph

  • smart object-mapping to reduce redundant requests to the database, improve latency and minimise wasted CPU cycles

  • user-definable session lifetimes, helping you to strike a balance between memory-usage and server request efficiency in your applications.

10.1.1. Overview

This reference documentation is broken down into sections to help the user understand specifics of how Neo4j-OGM works.

Getting started

Getting started can sometimes be a chore. What versions of Neo4j-OGM do you need? Where do you get them from? What build tool should you use? Getting Started is the perfect place to well…​ get started!


Drivers, logging, properties, configuration via Java. How to make sense of all the options? Configuration has got you covered.

Annotating your Domain Objects

To get started with your Neo4j-OGM application, you need only your domain model and the annotations provided by the library. You use annotations to mark domain objects to be reflected by nodes and relationships of the graph database. For individual fields the annotations allow you to declare how they should be processed and mapped to the graph. For property fields and references to other entities this is straightforward. Because Neo4j is a schema-free database, Neo4j-OGM uses a simple mechanism to map Java types to Neo4j nodes using labels. Relationships between entities are first class citizens in a graph database and therefore worth a section of it’s own describing their usage in Neo4j-OGM.

Connecting to the Database

Managing how you connect to the database is important. Connecting to the Database has all the details on what needs to happen to get you up and running.

Indexing and Primary Constraints

Indexing is an important part of any database. Neo4j-OGM provides a variety of features to support the management of Indexes as well as the ability to query your domain objects by something other than the internal Neo4j id. Indexing has everything you will want to know when it comes to getting that working.

Interacting with the Graph Model

Neo4j-OGM offers a session for interacting with the mapped entities and the Neo4j graph database. Neo4j uses transactions to guarantee the integrity of your data and Neo4j-OGM supports this fully. The implications of this are described in the transactions section. To use advanced functionality like Cypher queries, a basic understanding of the graph data model is required. The graph data model is explained in the chapter about in the introduction chapter.

Type Conversion

Neo4j-OGM provides support for default and bespoke type conversions, which allow you to configure how certain data types are mapped to nodes or relationships in Neo4j. See Type Conversion for more details.

Filtering your domain objects

Filters provides a simple API to append criteria to your stock Session.loadX() behaviour. This is covered in more detail in Filters.

Reacting to Persistence events

The Events mechanism allows users to register event listeners for handling persistence events related both to top-level objects being saved as well as connected objects. Event handling discusses all the aspects of working with events.

Testing in your application

Sometimes you want to be able to run your tests against an in-memory version of Neo4j-OGM. Testing goes into more detail of how to set that up.

Support for High Availability

For those using Neo4j Enterprise, support for high availability is extremely important. The chapter on High Availability goes into all the options Neo4j-OGM provides to support this.

10.2. Getting Started

10.2.1. Versions

Consult the version table to determine which version of Neo4j-OGM to use with a particular version of Neo4j and related technologies.

Neo4j-OGM Version Neo4j Version1


3.2.x, 3.3.x, 3.4.x, 3.5.x, 4.0.x2, 4.1.x2


3.1.x, 3.2.x, 3.3.x, 3.4.x


3.1.9, 3.2.12, 3.3.4, 3.4.4


2.3.9, 3.0.11, 3.1.6


2.3.8, 3.0.7


2.2.x, 2.3.x

1 The latest supported bugfix versions.

2 These versions are only supported over Bolt.

3 These versions are no longer actively developed.

4 These versions are no longer actively developed or supported.

Transitive dependencies

The following table list transitive dependencies between specific versions of projects related to Neo4j-OGM. When reporting issues or asking for help on StackOverflow or neo4j-users slack channel always verify versions used (e.g through mvn dependency:tree) and report them as well.

Spring Boot Version Spring Data Release Train Spring Data Neo4j Version Neo4j-OGM Version

























1 These versions are no longer actively developed.

2 These versions are no longer actively developed or supported.

Starting with Spring Boot 2.4, Spring Data Neo4j (version 6+) does not include Neo4j-OGM anymore.

10.2.2. Dependency Management

For building an application, your build automation tool needs to be configured to include the Neo4j-OGM dependencies.

Neo4j-OGM dependencies consist of neo4j-ogm-core, together with the relevant dependency declarations on the driver you want to use. Neo4j-OGM provides support for connecting to Neo4j by configuring one of the following Drivers:

  • neo4j-ogm-bolt-driver - Uses native Bolt protocol to communicate between Neo4j-OGM and a remote Neo4j instance.

  • neo4j-ogm-bolt-native-types - Support for all of Neo4j’s property types through the Bolt protocol.

  • neo4j-ogm-http-driver - Uses HTTP to communicate between Neo4j-OGM and a remote Neo4j instance.

  • neo4j-ogm-embedded-driver - Creates an in-memory Neo4j instance and uses it.

  • neo4j-ogm-embedded-native-types - Support for all of Neo4j’s property types in an embedded scenario.

Neo4j-OGM projects can be built using Maven, Gradle or any other build system that utilises Maven’s artifact repository structure.


In the <dependencies> section of your pom.xml add the following:

Maven dependencies

<!-- Only add if you're using the Bolt driver -->

<!-- Only add if you're using the HTTP driver -->

<!-- Only add if you're using the Embedded driver -->

Please also have a look at the native type system to take advantage of Neo4j-OGM’s support for native temporal and spatial types and how to use the modules neo4j-ogm-bolt-native-types and neo4j-ogm-embedded-native-types.


Ensure the following dependencies are added to you build.gradle:

Gradle dependencies
dependencies {
    compile 'org.neo4j:neo4j-ogm-core:{ogm-version}'
    runtime 'org.neo4j:neo4j-ogm-bolt-driver:{ogm-version}' // Only add if you're using the Bolt driver
    runtime 'org.neo4j:neo4j-ogm-http-driver:{ogm-version}' // Only add if you're using the HTTP driver
    runtime 'org.neo4j:neo4j-ogm-embedded-driver:{ogm-version}' //  Only add if you're using the Embedded driver
    runtime 'org.neo4j:neo4j:{neo4j-version}' //  Only add if you're using the Embedded driver

10.3. Configuration

10.3.1. Configuration method

There are several ways to supply configuration to Neo4j-OGM:

  • using a properties file

  • programmatically using Java

  • by providing an already configured Neo4j Java driver instance

These methods are described below. They are also available as code in the examples.

Using a properties file

Properties file on classpath:

ConfigurationSource props = new ClasspathConfigurationSource("my.properties");
Configuration configuration = new Configuration.Builder(props).build();

Properties file on filesystem:

ConfigurationSource props = new FileConfigurationSource("/etc/my.properties");
Configuration configuration = new Configuration.Builder(props).build();
Programmatically using Java

In cases where you are not be able to provide configuration via a properties file you can configure Neo4j-OGM programmatically instead.

The Configuration object provides a fluent API to set various configuration options. This object then needs to be supplied to the SessionFactory constructor in order to be configured.

By providing a Neo4j driver instance

Just configure the driver as you would do for direct access to the database, and pass the driver instance to the session factory.

This method allows the greatest flexibility and gives you access to the full range of low level configuration options.

Example providing a bolt driver instance to Neo4j-OGM
org.neo4j.driver.v1.Driver nativeDriver = ...;
Driver ogmDriver = new BoltDriver(nativeDriver);
new SessionFactory(ogmDriver, ...);

10.3.2. Driver Configuration

For configuration through properties file or configuration builder the driver is automatically inferred from given URI. Empty URI means embedded driver with impermanent database.

HTTP Driver
Table 3. Basic HTTP Driver Configuration
ogm.properties Java Configuration
Configuration configuration = new Configuration.Builder()
Bolt Driver

Note that for the URI, if no port is specified, the default Bolt port of 7687 is used. Otherwise, a port can be specified with bolt://neo4j:password@localhost:1234.

Also, the bolt driver allows you to define a connection pool size, which refers to the maximum number of sessions per URL. This property is optional and defaults to 50.

Table 4. Basic Bolt Driver Configuration
ogm.properties Java Configuration
Configuration configuration = new Configuration.Builder()

A timeout to the database with the Bolt driver can be set by updating your Database’s neo4j.conf. The exact setting to change can be found here.

Embedded Driver

You should use the Embedded driver if you don’t want to use a client-server model, or if your application is running as a Neo4j Unmanaged Extension. You can specify a permanent data store location to provide durability of your data after your application shuts down, or you can use an impermanent data store, which will only exist while your application is running.

As of 2.1.0 the Neo4j-OGM embedded driver no longer ships with the Neo4j kernel. Users are expected to provide this dependency through their dependency management system. See Getting Started for more details.
Table 5. Permanent Data Store Embedded Driver Configuration
ogm.properties Java Configuration
Configuration configuration = new Configuration.Builder()

To use an impermanent data store which will be deleted on shutdown of the JVM, you just omit the URI attribute.

Table 6. Impermanent Data Store Embedded Driver Configuration
ogm.properties Java Configuration
# Leave empty
Configuration configuration = new Configuration.Builder().build()
Configuration of the embedded instance

The embedded instance of Neo4j can be configured through a standard neo4j.conf file. A neo4j.conf file is a properties based configuration format. Neo4j’s available configuration properties are listed in the product manual. Not all of them are applicable to an embedded scenario.

You can pass the location of a configuration file either through ogm.properties or programmatically. Both file and classpath-resources are supported. Resource location without a protocol prefix are assumed to be classpath resources.

Table 7. Providing the location of a Neo4j configuration file
ogm.properties Java Configuration
# Looks in the root of the classpath

# Explicitly in the classpath
# neo4j.conf.location=classpath:neo4j.conf

# Or as file URL
# neo4j.conf.location=file:///config/neo4j.conf
String neo4jConfLocation;

​// Choose one:
​// Looks in the root of the classpath
neo4jConfLocation = "neo4j.conf"

​// Explicitly in the classpath
​// neo4jConfLocation = "classpath:neo4j.conf"

​// Or as file URL
​// neo4jConfLocation = "file:///config/neo4j.conf"

Configuration configuration =
    new Configuration.Builder()
By setting dbms.config=HA in the configuration file for Neo4j, you can enable HA mode of the embedded instance. You need to have the required enterpris dependencies on the classpath. For Neo4j 3.4 those are org.neo4j:neo4j-ha and org.neo4j:neo4j-enterprise, for 3.5 it’s only com.neo4j:neo4j-enterprise.
Configuration of an unmanaged extension

The OgmPluginInitializer class was deprecated in Neo4j-OGM 3.2 and will be removed in the next major version. To use Neo4j-OGM within an unmanaged extension you connect to the database the usual way you would do with an embedded driver.


If you are using the HTTP or Bolt Driver you have a number of different ways to supply credentials to the Driver Configuration.

ogm.properties Java Configuration
# embedded

# separately
Configuration configuration = new Configuration.Builder()

Configuration configuration = new Configuration.Builder()
             .credentials("user", "password")

Note: Currently only Basic Authentication is supported by Neo4j-OGM. If you need to use more advanced authentication scheme, use the native driver configuration method.

Transport Layer Security (TLS/SSL)

The Bolt and HTTP drivers also allow you to connect to Neo4j over a secure channel. These rely on Transport Layer Security (aka TLS/SSL) and require the installation of a signed certificate on the server.

In certain situations (e.g. some cloud environments) it may not be possible to install a signed certificate even though you still want to use an encrypted connection.

To support this, both drivers have configuration settings allowing you to bypass certificate checking, although they differ in their implementation.

Both of these strategies leave you vulnerable to a MITM attack. You should probably not use them unless your servers are behind a secure firewall.
ogm.properties Java Configuration
#Encryption level (TLS), optional, defaults to REQUIRED.
#Valid values are NONE,REQUIRED

#Trust strategy, optional, not used if not specified.

#Trust certificate file, required if trust.strategy is specified
Configuration config = new Configuration.Builder()

TRUST_ON_FIRST_USE means that the Bolt Driver will trust the first connection to a host to be safe and intentional. On subsequent connections, the driver will verify that the host is the same as on that first connection.

ogm.properties Java Configuration
trust.strategy = ACCEPT_UNSIGNED
Configuration configuration = new Configuration.Builder()

The ACCEPT_UNSIGNED strategy permits the HTTP Driver to accept Neo4j’s default snakeoil.cert (and any other) unsigned certificate when connecting over HTTPS.

Bolt connection testing

In order to prevent some network problems while accessing a remote database, you may want to tell the Bolt driver to test connections from the connection pool.

This is particularly useful when there are firewalls between the application tier and the database.

You can do that with the connection liveness parameter which indicates the interval at which the connections will be tested. A value of 0 indicates that the connection will always be tested. A negative value indicates that the connection will never be tested.

ogm.properties Java Configuration
# interval, in milliseconds, to check for stale db connections (test-on-borrow)
Configuration config = new Configuration.Builder()
Eager connection verification

OGM by default does not connect to Neo4j server on application startup. This allows you to start the application and database independently and Neo4j will be accessed on first read/write. To change this behaviour set the property verify.connection (or Builder.verifyConnection(boolean)) to true. This settings is valid only for Bolt and HTTP drivers.

10.3.3. Logging

Neo4j-OGM uses SLF4J to log statements. In production, you can set the log level in a file called logback.xml to be found at the root of the classpath. Please see the Logback manual for further details.

10.4. Annotating Entities

10.4.1. @NodeEntity: The basic building block

The @NodeEntity annotation is used to declare that a POJO class is an entity backed by a node in the graph database. Entities handled by Neo4j-OGM must have one empty public constructor to allow the library to construct the objects.

Fields on the entity are by default mapped to properties of the node. Fields referencing other node entities (or collections thereof) are linked with relationships.

@NodeEntity annotations are inherited from super-types and interfaces. It is not necessary to annotate your domain objects at every inheritance level.

Entity fields can be annotated with annotations like @Property, @Id, @GeneratedValue, @Transient or @Relationship. All annotations live in the org.neo4j.ogm.annotation package. Marking a field with the transient modifier has the same effect as annotating it with @Transient; it won’t be persisted to the graph database.

Persisting an annotated entity
public class Actor extends DomainObject {

   @Id @GeneratedValue
   private Long id;

   private String fullName;

   @Property("age") // using value attribute to have a shorter definition
   private int age;

   @Relationship(type="ACTED_IN", direction=Relationship.OUTGOING)
   private List<Movie> filmography;


public class Movie {

   @Id @GeneratedValue Long id;

   private String name;


The default label is the simple class name of the annotated entity. There are some rules to determine if parent classes also contribute their label to the child class:

  • the parent class is a non-abstract class (the existing of @NodeEntity is optional)

  • the parent class is an abstract class and has a @NodeEntity annotation

  • java.lang.Object will be ignored

  • interfaces do not create an additional label

If the label (as you can see in the example above) or the value attribute of the @NodeEntity annotation is set it will replace the default label applied to the node in the database.

Saving a simple object graph containing one actor and one film using the above annotated objects would result in the following being persisted in Neo4j.

(:Actor:DomainObject {name:'Tom Cruise'})-[:ACTED_IN]->(:Film {title:'Mission Impossible'})

When annotating your objects, you can choose to NOT apply the annotations on the fields. OGM will then use conventions to determine property names in the database for each field.

Persisting a non-annotated entity
public class Actor extends DomainObject {

   private Long id;
   private String fullName;
   private List<Movie> filmography;


public class Movie {

   private Long id;
   private String name;


In this case, a graph similar to the following would be persisted.

(:Actor:DomainObject {fullName:'Tom Cruise'})-[:FILMOGRAPHY]->(:Movie {name:'Mission Impossible'})

While this will map successfully to the database, it’s important to understand that the names of the properties and relationship types are tightly coupled to the class’s member names. Renaming any of these fields will cause parts of the graph to map incorrectly, hence the recommendation to use annotations.

Please read Non-annotated properties and best practices for more details and best practices on this.

@Properties: dynamically mapping properties to graph

A @Properties annotation tells Neo4j-OGM to map values of a Map field in a node or relationship entity to properties of a node or a relationship in the graph.

The property names are derived from field name or prefix, delimiter and keys in the Map. For example Map field with name address containing following entries:

"street" => "Downing Street"
"number" => 10

will map to following node/relationship properties

address.street=Downing Street

Supported types for keys in the Map are String and Enum.

The values in the Map can be of any Java type equivalent to Cypher types. If full type information is provided other Java types are also supported.

If annotation parameter allowCast is set to true then types that can be cast to corresponding Cypher types are allowed as well.

The original type cannot be deduced and the value will be deserialized to corresponding type - e.g. when Integer instance is put to Map<String, Object> it will be deserialized as Long.
public class Student {

    private Map<String, Integer> properties = new HashMap<>();

    private Map<String, Object> properties = new HashMap<>();

Runtime managed labels

As stated above, the label applied to a node is the contents of the @NodeEntity label property, or if not specified, it will default to the simple class name of the entity. Sometimes it might be necessary to add and remove additional labels to a node at runtime. We can do this using the @Labels annotation. Let’s provide a facility for adding additional labels to the Student entity:

public class Student {

    private List<String> labels = new ArrayList<>();


Now, upon save, the node’s labels will correspond to the entity’s class hierarchy plus whatever the contents of the backing field are. We can use one @Labels field per class hierarchy - it should be exposed or hidden from sub-classes as appropriate.

Runtime labels must not conflict with static labels defined on node entities.

In a typical situation Neo4j-OGM issues one request per node entity type when saving node entities to the database. Using many distinct labels will result into many requests to the database (one request per unique combination of labels).

10.4.2. @Relationship: Connecting node entities

Every field of an entity that references one or more other node entities is backed by relationships in the graph. These relationships are managed by Neo4j-OGM automatically.

The simplest kind of relationship is a single object reference pointing to another entity (1:1). In this case, the reference does not have to be annotated at all, although the annotation may be used to control the direction and type of the relationship. When setting the reference, a relationship is created when the entity is persisted. If the field is set to null, the relationship is removed.

Single relationship field
public class Movie {
    private Actor topActor;

It is also possible to have fields that reference a set of entities (1:N). Neo4j-OGM supports the following types of entity collections:

  • java.util.Vector

  • java.util.List, backed by a java.util.ArrayList

  • java.util.SortedSet, backed by a java.util.TreeSet

  • java.util.Set, backed by a java.util.HashSet

  • Arrays

Node entity with relationships
public class Actor {
    @Relationship(type = "TOP_ACTOR", direction = Relationship.INCOMING)
    private Set<Movie> topActorIn;

    @Relationship("ACTS_IN") // same meaning as above but using the value attribute
    private Set<Movie> movies;

For graph to object mapping, the automatic transitive loading of related entities depends on the depth of the horizon specified on the call to Session.load(). The default depth of 1 implies that related node or relationship entities will be loaded and have their properties set, but none of their related entities will be populated.

If this Set of related entities is modified, the changes are reflected in the graph once the root object (Actor, in this case) is saved. Relationships are added, removed or updated according to the differences between the root object that was loaded and the corresponding one that was saved..

Neo4j-OGM ensures by default that there is only one relationship of a given type between any two given entities. The exception to this rule is when a relationship is specified as either OUTGOING or INCOMING between two entities of the same type. In this case, it is possible to have two relationships of the given type between the two entities, one relationship in either direction.

If you don’t care about the direction then you can specify direction=Relationship.UNDIRECTED which will guarantee that the path between two node entities is navigable from either side.

For example, consider the PARTNER relationship between two companies, where (A)-[:PARTNER_OF]→(B) implies (B)-[:PARTNER_OF]→(A). The direction of the relationship does not matter; only the fact that a PARTNER_OF relationship exists between these two companies is of importance. Hence an UNDIRECTED relationship is the correct choice, ensuring that there is only one relationship of this type between two partners and navigating between them from either entity is possible.

The direction attribute on a @Relationship defaults to OUTGOING. Any fields or methods backed by an INCOMING relationship must be explicitly annotated with an INCOMING direction.

Using more than one relationship of the same type

In some cases, you want to model two different aspects of a conceptual relationship using the same relationship type. Here is a canonical example:

Clashing Relationship Type
class Person {
    private Long id;
    private Car car;

    private Pet pet;

This will work just fine, however, please be aware that this is only because the end node types (Car and Pet) are different types. If you wanted a person to own two cars, for example, then you’d have to use a Collection of cars or use differently-named relationship types.

Ambiguity in relationships

In cases where the relationship mappings could be ambiguous, the recommendation is that:

  • The objects be navigable in both directions.

  • The @Relationship annotations are explicit.

Examples of ambiguous relationship mappings are multiple relationship types that resolve to the same types of entities, in a given direction, but whose domain objects are not navigable in both directions.


Neo4j doesn’t have any ordering on relationships, so the relationships are fetched without any specific ordering. If you want to impose order on collections of relationships you have several options:

  • use a SortedSet and implement Comparable

  • sort relationships in @PostLoad annotated method

You can sort either by a property of a related node or by relationship property. To sort by relationship property you need to use a relationship entity. See @RelationshipEntity: Rich relationships.

10.4.3. @RelationshipEntity: Rich relationships

To access the full data model of graph relationships, POJOs can also be annotated with @RelationshipEntity, making them relationship entities. Just as node entities represent nodes in the graph, relationship entities represent relationships. Such POJOs allow you to access and manage properties on the underlying relationships in the graph.

Fields in relationship entities are similar to node entities, in that they’re persisted as properties on the relationship. For accessing the two endpoints of the relationship, two special annotations are available: @StartNode and @EndNode. A field annotated with one of these annotations will provide access to the corresponding endpoint, depending on the chosen annotation.

For controlling the relationship-type a String attribute called type is available on the @RelationshipEntity annotation. Like the simple strategy for labelling node entities, if this is not provided then the name of the class is used to derive the relationship type, although it’s converted into SNAKE_CASE to honour the naming conventions of Neo4j relationships. As of the current version of Neo4j-OGM, the type must be specified on the @RelationshipEntity annotation as well as its corresponding @Relationship annotations. This can also be done without naming the attribute but only providing the value.

You must include @RelationshipEntity plus exactly one @StartNode field and one @EndNode field on your relationship entity classes or Neo4j-OGM will throw a MappingException when reading or writing. It is not possible to use relationship entities in a non-annotated domain model.

A simple Relationship entity
public class Actor {
    Long id;
    @Relationship(type="PLAYED_IN") private Role playedIn;

@RelationshipEntity(type = "PLAYED_IN")
public class Role {
    @Id @GeneratedValue   private Long relationshipId;
    @Property  private String title;
    @StartNode private Actor actor;
    @EndNode   private Movie movie;

public class Movie {
    private Long id;
    private String title;

Note that the Actor also contains a reference to a Role. This is important for persistence, even when saving the Role directly, because paths in the graph are written starting with nodes first and then relationships are created between them. Therefore, you need to structure your domain models so that relationship entities are reachable from node entities for this to work correctly.

Additionally, Neo4j-OGM will not persist a relationship entity that doesn’t have any properties defined. If you don’t want to include properties in your relationship entity then you should use a plain @Relationship instead. Multiple relationship entities which have the same property values and relate the same nodes are indistinguishable from each other and are represented as a single relationship by Neo4j-OGM.

The @RelationshipEntity annotation must appear on all leaf subclasses if they are part of a class hierarchy representing relationship entities. This annotation is optional on superclasses.

A note on JSON serialization

Looking at the example given above the circular dependency on the class level between the node and the rich relationship can easily be spotted. It will not have any effect on your application as long as you do not serialize the objects. One kind of serialization that is used today is JSON serialization using the Jackson mapper. This mapper library is often used in connection with other frameworks like Spring or Java EE and their corresponding web modules. Traversing the object tree it will hit the part when it visits a Role after visiting an Actor. Obvious it will then find the Actor object and visit this again, and so on. This will end up in a StackOverflowError. To break this parsing cycle it is mandatory to support the mapper by providing annotation to your class(es). This can be done by adding either @JsonIgnore on the property that causes the loop or @JsonIgnoreProperties.

Suppress infinite traversing
public class Actor {
    Long id;

    // Needs knowledge about the attribute "title" in the relationship.
    // Applying JsonIgnoreProperties like this ignores properties of the attribute itself.
    @Relationship(type="PLAYED_IN") private Role playedIn;

public class Role {
    @Id @GeneratedValue private Long relationshipId;
    @Property private String title;

    // Direct way to suppress the serialization.
    // This ignores the whole actor attribute.
    @StartNode private Actor actor;

    @EndNode   private Movie movie;

10.4.4. Entity identifier

Every node and relationship persisted to the graph must have an ID. Neo4j-OGM uses this to identify and re-connect the entity to the graph in memory. Identifier may be either a primary id or a native graph id (the technical id attributed by Neo4j at node creation time).

For primary id use the @Id on a field of any supported type or a field with provided AttributeConverter. A unique index is created for such property (if index creation is enabled). User code should either set the id manually when the entity instance is created or id generation strategy should be used. It is not possible to store an entity with null id value and no generation strategy.

Specifying primary id on a relationship entity is possible, but lookups by this id are slow, because Neo4j database doesn’t support schema indexes on relationships.

For native graph id use @Id @GeneratedValue (with default strategy InternalIdStrategy). The field type must be Long. This id is assigned automatically upon saving the entity to the graph and user code should never assign a value to it.

It must not be a primitive type because then an object in a transient state cannot be represented, as the default value 0 would point to the reference node.

Do not rely on this ID for long running applications. Neo4j will reuse deleted node ID’s. It is recommended users come up with their own unique identifier for their domain objects (or use a UUID).

An entity can be looked up by this either type of id by using Session.load(Class<T>, ID) and Session.loadAll(Class<T>, Collection<ID>) methods.

It is possible to have both natural and native id in one entity. In such situation lookups prefer the primary id.

If the field of type Long is simply named 'id' then it is not necessary to annotate it with @Id @GeneratedValue as Neo4j-OGM will use it automatically as native id.

Entity Equality

Entity equality can be a grey area. There are many debatable issues, such as whether natural keys or database identifiers best describe equality and the effects of versioning over time. Neo4j-OGM does not impose a dependency upon a particular style of equals() or hashCode() implementation. The native or custom id field are directly checked to see if two entities represent the same node and a 64-bit hash code is used for dirty checking, so you’re not forced to write your code in a certain way!

You should write your equals and hashCode in a domain specific way for managed entities. We strongly advise developers to not use the native id described by a Long field in combination with @Id @GeneratedValue in these methods. This is because when you first persist an entity, its hashcode changes because Neo4j-OGM populates the database ID on save. This causes problems if you had inserted the newly created entity into a hash-based collection before saving.
Id Generation Strategy

If the @Id annotation is used on its own it is expected that the field will be set by the application code. To automatically generate and assign a value of the property the annotation @GeneratedValue can be used.

The @GeneratedValue annotation has optional parameter strategy, which can be used to provide a custom id generation strategy. The class must implement org.neo4j.ogm.id.IdStrategy interface. The strategy class can either supply no argument constructor - in which case Neo4j-OGM will create an instance of the strategy and call it. For situations where some external context is needed an externally created instance can be registered with SessionFactory by using SessionFactory.register(IdStrategy).

10.4.5. Optimistic locking with @Version annotation

Optimistic locking is supported by Neo4j-OGM to provide concurrency control. To use optimistic locking define a field annotated with @Version annotation. The field is then managed by Neo4j-OGM and used to perform optimistic locking checks when updating entities. The type of the field must be Long and an entity may contain only one such field.

Typical scenario where optimistic locking is used then looks like follows:

  • new object is created, version field contains null value

  • when the object is saved the version field is set to 0 by Neo4j-OGM

  • when a modified object is saved the version provided in the object is checked against a version in the database during the update, if successful then the version is incremented both in the object and in the database

  • if another transaction modified the object in the meantime (and therefore incremented the version) then this is detected and an OptimisticLockingException is thrown

Optimistic locking check is performed for

  • updating properties of nodes and relationship entities

  • deleting nodes via Session.delete(T)

  • deleting relationship entities via Session.delete(T)

  • deleting relationship entities detected through Session.save(T)

When an optimistic locking failure happens following operations are performed on the Session:

  • object which failed the optimistic locking check is removed from the context so it can be reloaded

  • in case a default transaction is used it is rolled back

  • in case a manual transaction is used then it is not rolled back, but because the update may contain multiple statements which are checked eagerly it is not defined what updates were actually performed in the database and it is advised to rollback the transaction. If you know you updates consists of single modification you may however choose to reload the object and continue the transaction.

10.4.6. @Property: Optional annotation for property fields

As we touched on earlier, it is not necessary to annotate property fields as they are persisted by default. Fields that are annotated as @Transient or with transient are exempted from persistence. All fields that contain primitive values are persisted directly to the graph. All fields convertible to a String using the conversion services will be stored as a string. Neo4j-OGM includes default type converters for commonly used types, for a full list see Built-in type conversions.

Custom converters are also specified by using @Convert - this is discussed in detail later on.

Collections of primitive or convertible values are stored as well. They are converted to arrays of their type or strings respectively.

Node property names can be explicitly assigned by setting the name attribute. For example @Property(name="last_name") String lastName. The node property name defaults to the field name when not specified.

Property fields to be persisted to the graph must not be declared final.

10.4.7. @PostLoad

A method annotated with @PostLoad will be called once the entity is loaded from the database.

10.4.8. Non-annotated properties and best practices

Neo4j-OGM supports mapping annotated and non-annotated objects models. It’s possible to save any POJO without annotations to the graph, as the framework applies conventions to decide what to do. This is useful in cases when you don’t have control over the classes that you want to persist. The recommended approach, however, is to use annotations wherever possible, since this gives greater control and means that code can be refactored safely without risking breaking changes to the labels and relationships in your graph.

The support for non-annotated domain classes might be dropped in the future, to allow startup optimizations.

Annotated and non-annotated objects can be used within the same project without issue.

The object graph mapping comes into play whenever an entity is constructed from a node or relationship. This could be done explicitly during the lookup or create operations of the Session but also implicitly while executing any graph operation that returns nodes or relationships and expecting mapped entities to be returned.

Entities handled by Neo4j-OGM must have one empty public constructor to allow the library to construct the objects.

Unless annotations are used to specify otherwise, the framework will attempt to map any of an object’s "simple" fields to node properties and any rich composite objects to related nodes. A "simple" field is any primitive, boxed primitive or String or arrays thereof, essentially anything that naturally fits into a Neo4j node property. For related entities the type of a relationship is inferred by the bean property name.

10.5. Indexing

Indexing is used in Neo4j to quickly find nodes and relationships from which to start graph operations.

10.5.1. Indexes and Constraints

Indexes based on labels and properties are supported with the @Index annotation. Any property field annotated with @Index will have an appropriate schema index created. For @Index(unique=true) a constraint is created.

You may add as many indexes or constraints as you like to your class. A class outside any inheritance hierarchy leads to the creation of indexes for its annotated fields on its label. A class inheriting from a super-class and declaring an index on a field shadowing the same field of the super class leads to the creation of an index for that field on it’s own label. A non-abstract super-class will index that field on it’s corresponding label as well. In cases where there is no index definition in a sub-class at al, the first index-defining super class will define the index on its label in the database.

10.5.2. Primary Constraints

The primary property of the @Index annotation is deprecated since Neo4j-OGM 3 and should not be used. The primary key is solely provided by the @Id annotation. See Entity identifier for more information.

10.5.3. Composite Indexes and Node Key Constraints

Composite indexes based on label and multiple properties are supported with @CompositeIndex annotation. The annotation is to be placed at the class level. All properties specified must exist within the class or one of its superclasses. It is possible to create multiple composite indexes by repeating the annotation.

Providing unique=true parameter will create a node key constraint instead of a composite index.

This feature is only supported by Neo4j Enterprise 3.2 and higher.

10.5.4. Existence constraints

Existence constraints for a property is supported with @Required annotation. It is possible to annotate properties in both node entities and relationship entities. For node entities the label of declaring class is used to create the constraint. For relationship entities the relationship type is used - such type must be defined on leaf class.

This feature is only supported by Neo4j Enterprise 3.1 and higher.

10.5.5. Index Creation

By default index management is set to None.

From our experience with this feature usage we see this as an development time feature. Usually indexes should get created within the database. At most in test scenarios there is no guarantee that an index is created before the test runs because of its asynchronous creation.

If you would like Neo4j-OGM to manage your schema creation there are several ways to go about it.

Only classes marked with @Index, @CompositeIndex or @Required will be used. Indexes will always be generated with the containing class’s label and the annotated property’s name. An abstract class containing indexes or constraints must have @NodeEntity annotation present. Index generation behaviour can be defined in ogm.properties by defining a property called: indexes.auto and providing a value of:

Below is a table of all options available for configuring Auto-Indexing.

Option Description Properties Example Java Example

none (default)

Nothing is done with index and constraint annotations.




Make sure the connected database has all indexes and constraints in place before starting up




Drops all constraints and indexes on startup then builds indexes based on whatever is represented in Neo4j-OGM by @Index. Handy during development.




Builds indexes based on whatever is represented in Neo4j-OGM by @Index. Indexes will be changed to constraints and vise versa if the definition in db differs from metadata. Handy during development




Dumps the generated constraints and indexes to a file. Good for setting up environments. none: Default. Simply marks the field as using an index.

indexes.auto=dump indexes.auto.dump.dir=<a directory> indexes.auto.dump.filename=<a filename>

config.setAutoIndex("dump"); config.setDumpDir("XXX"); config.setDumpFilename("XXX");

10.6. Connecting to the Graph

In order to interact with mapped entities and the Neo4j graph, your application will require a Session, which is provided by the SessionFactory.

10.6.1. SessionFactory

The SessionFactory is needed by Neo4j-OGM to create instances of Session as required. This also sets up the object-graph mapping metadata when constructed, which is then used across all Session objects that it creates. The packages to scan for domain object metadata should be provided to the SessionFactory constructor.

The SessionFactory is an expensive object to create because it scans all the requested packages to build up metadata. It should typically be set up once during life of your application.
Create SessionFactory with Configuration instance

As seen in the configuration section, this is done by providing the SessionFactory a configuration object:

SessionFactory sessionFactory = new SessionFactory(configuration, "com.mycompany.app.domainclasses");
Create SessionFactory with Driver instance

This can be done by providing to the SessionFactory a driver instance:

SessionFactory sessionFactory = new SessionFactory(driver, "com.mycompany.app.domainclasses");
Embedded driver instance

If a pre-configured embedded database is needed, it can be passed into the embedded driver. It is possible to either use a configuration file

GraphDatabaseService db = new GraphDatabaseFactory()
            .newEmbeddedDatabaseBuilder(new File(storeDir))

or set the setting parameters programmatically.

GraphDatabaseService db = new GraphDatabaseFactory()
            .newEmbeddedDatabaseBuilder(new File(storeDir))
            .setConfig( GraphDatabaseSettings.pagecache_memory, "512M" )

and pass them into the EmbeddedDriver.

EmbeddedDriver driver = new EmbeddedDriver(db)

SessionFactory sessionFactory = new SessionFactory(driver, "com.mycompany.app.domainclasses");
Multiple entity packages

Multiple packages may be provided as well. If you would rather just pass in specific classes you can also do that via an overloaded constructor.

Multiple packages
SessionFactory sessionFactory = new SessionFactory(configuration, "first.package.domain", "second.package.domain",...);

10.7. Using Neo4j-OGM Session

The Session provides the core functionality to persist objects to the graph and load them in a variety of ways.

10.7.1. Session Configuration

A Session is used to drive the object-graph mapping framework. It keeps track of the changes that have been made to entities and their relationships. The reason it does this is so that only entities and relationships that have changed get persisted on save, which is particularly efficient when working with large graphs. Once an entity is tracked by the session, reloading this entity within the scope of the same session will result in the session cache returning the previously loaded entity. However, the subgraph in the session will expand if the entity or its related entities retrieve additional relationships from the graph.

The lifetime of the Session can be managed in code. For example, associated with single fetch-update-save cycle or unit of work.

If your application relies on long-running sessions then you may not see changes made from other users and find yourself working with outdated objects. On the other hand, if your sessions have a too narrow scope then your save operations can be unnecessarily expensive, as updates will be made to all objects if the session isn’t aware of the those that were originally loaded.

There’s therefore a trade off between the two approaches. In general, the scope of a Session should correspond to a "unit of work" in your application.

If you want to fetch fresh data from the graph, then this can be achieved by using a new session or clearing the current sessions context using Session.clear(). This feature should be used with caution because it will clear the whole cache and it needs to get rebuild on the next operation. Also Neo4j-OGM won’t be able to do any dirty tracking between the operations that are separated by the Session.clear() call.

10.7.2. Basic operations

Basic operations are limited to CRUD operations on entities and executing arbitrary Cypher queries; more low-level manipulation of the graph database is not possible.

Given that the Neo4j-OGM framework is driven by Cypher queries alone, there’s no way to work directly with Node and Relationship objects in remote server mode.

If you find yourself in trouble because of the omission of these features, then your best option is to write a Cypher query to perform the operations on the nodes/relationships instead.

In general, for low-level, very high-performance operations like complex graph traversals you will get the best performance by writing a server-side extension. For most purposes, though, Cypher will be performant and expressive enough to perform the operations that you need.

10.7.3. Persisting entities

Session allows to save, load, loadAll and delete entities with transaction handling and exception translation managed for you. The eagerness with which objects are retrieved is controlled by specifying the depth argument to any of the load methods.

Entity persistence is performed through the save() method on the underlying Session object.

Under the bonnet, the implementation of Session has access to the MappingContext that keeps track of the data that has been loaded from Neo4j during the lifetime of the session. Upon invocation of save() with an entity, it checks the given object graph for changes compared with the data that was loaded from the database. The differences are used to construct a Cypher query that persists the deltas to Neo4j before repopulating it’s state based on the response from the database server.

Neo4j-OGM doesn’t automatically commit when a transaction closes, so an explicit call to save(…​) is required in order to persist changes to the database.

Example 60. Persisting entities
public class Person {
   private String name;
   public Person(String name) {
      this.name = name;

// Store Michael in the database.
Person p = new Person("Michael");
Save depth

As mentioned previously, save(entity) is overloaded as save(entity, depth), where depth dictates the number of related entities to save starting from the given entity. The default depth, -1, will persist properties of the specified entity as well as every modified entity in the object graph reachable from it. This means that all affected objects in the entity model that are reachable from the root object being persisted will be modified in the graph. This is the recommended approach because it means you can persist all your changes in one request. Neo4j-OGM is able to detect which objects and relationships require changing, so you won’t flood Neo4j with a bunch of objects that don’t require modification. You can change the persistence depth to any value, but you should not make it less than the value used to load the corresponding data or you run the risk of not having changes you expect to be made actually being persisted in the graph. A depth of 0 will persist only the properties of the specified entity to the database. Please be aware that a depth of 0 for a relationship operation will always also affect the linked nodes.

Specifying the save depth is handy when it comes to dealing with complex collections, that could potentially be very expensive to load.

Example 61. Relationship save cascading
class Movie {
    String title;
    Actor topActor;
    public void setTopActor(Actor actor) {
        topActor = actor;

class Actor {
    String name;

Movie movie = new Movie("Polar Express");
Actor actor = new Actor("Tom Hanks");


Neither the actor nor the movie has been assigned a node in the graph. If we were to call session.save(movie), then Neo4j-OGM would first create a node for the movie. It would then note that there is a relationship to an actor, so it would save the actor in a cascading fashion. Once the actor has been persisted, it will create the relationship from the movie to the actor. All of this will be done atomically in one transaction.

The important thing to note here is that if session.save(actor) is called instead, then only the actor will be persisted. The reason for this is that the actor entity knows nothing about the movie entity - it is the movie entity that has the reference to the actor. Also note that this behaviour is not dependent on any configured relationship direction on the annotations. It is a matter of Java references and is not related to the data model in the database.

In the following example, the actor and the movie are both managed entities, having both been previously persisted to the graph:

Example 62. Cascade for modified fields

In this case, even though the movie has a reference to the actor, the property change on the actor will be persisted by the call to save(movie). The reason for this is, as mentioned above, that cascading will be done for fields that have been modified and reachable from the root object being saved.

In the example below, session.save(user,1) will persist all modified objects reachable from user up to one level deep. This includes posts and groups but not entities related to them, namely author, comments, members or location. A persistence depth of 0 i.e. session.save(user,0) will save only the properties on the user, ignoring any related entities. In this case, fullName is persisted but not friends, posts or groups.

Persistence Depth
public class User  {

   private Long id;
   private String fullName;
   private List<Post> posts;
   private List<Group> groups;


public class Post {

   private Long id;
   private String name;
   private String content;
   private User author;
   private List<Comment> comments;


public class Group {

   private Long id;
   private String name;
   private List<User> members;
   private Location location;


10.7.4. Loading Entities

Entities can be loaded from Neo4j-OGM through the use of the session.loadXXX() methods or via session.query()/session.queryForObject() which will accept your own Cypher queries (See section below on cypher queries).

Neo4j-OGM includes the concept of persistence horizon (depth). On any individual request, the persistence horizon indicates how many relationships should be traversed in the graph when loading or saving data. A horizon of zero means that only the root object’s properties will be loaded or saved, a horizon of 1 will include the root object and all its immediate neighbours, and so on. This attribute is enabled via a depth argument available on all session methods, but Neo4j-OGM chooses sensible defaults so that you don’t have to specify the depth attribute unless you want change the default values.

Load depth

By default, loading an instance will map that object’s simple properties and its immediately-related objects (i.e. depth = 1). This helps to avoid accidentally loading the entire graph into memory, but allows a single request to fetch not only the object of immediate interest, but also its closest neighbours, which are likely also to be of interest. This strategy attempts to strike a balance between loading too much of the graph into memory and having to make repeated requests for data.

If parts of your graph structure are deep and not broad (for example a linked-list), you can increase the load horizon for those nodes accordingly. Finally, if your graph will fit into memory, and you’d like to load it all in one go, you can set the depth to -1.

On the other hand when fetching structures which are potentially very "bushy" (e.g. lists of things that themselves have many relationships), you may want to set the load horizon to 0 (depth = 0) to avoid loading thousands of objects most of which you won’t actually inspect.

When loading entities with a custom depth less than the one used previously to load the entity within the session, existing relationships will not be flushed from the session; only new entities and relationships are added. This means that reloading entities will always result in retaining related objects loaded at the highest depth within the session for those entities. If it is required to load entities with a lower depth than previously requested, this must be done on a new session, or after clearing your current session with Session.clear().

Query Strategy

WhenNeo4j-OGM loads entities through load* methods (including ones with filters) it uses LoadStrategy to generate the RETURN part of the query.

Available load strategies are

  • schema load strategy - uses metadata on domain entities and pattern comprehensions to retrieve nodes and relationships (default since Neo4j-OGM 3.0)

  • path load strategy - uses paths from root node to fetch related nodes, p=(n)-[0..]-() (default before Neo4j-OGM 3.0)

The strategy can be overridden globally by calling SessionFactory.setLoadStrategy(strategy) or for single session only (e.g. when different strategy is more effective for given query) by calling Session.setLoadStrategy(strategy)

Cypher queries

Cypher is Neo4j’s powerful query language. It is understood by all the different drivers in Neo4j-OGM which means that your application code should run identically, whichever driver you choose to use. This makes application development much easier: you can use the Embedded Driver for your integration tests, and then plug in the HTTP Driver or the Bolt Driver when deploying your code into a production client-server environment.

The Session also allows execution of arbitrary Cypher queries via its query and queryForObject methods. Cypher queries that return tabular results should be passed into the query method which returns an Result. This consists of QueryStatistics representing statistics of modifying cypher statements if applicable, and an Iterable<Map<String,Object>> containing the raw data, which can be either used as-is or converted into a richer type if needed. The keys in each Map correspond to the names listed in the return clause of the executed Cypher query.

queryForObject specifically queries for entities and as such, queries supplied to this method must return nodes and not individual properties.

Query methods that retrieve mapped objects may be used in cases where the query generated by load strategy does not have sufficient performance.

Such queries should return nodes and optionally relationships. For a relationship to be mapped both start and end node must be returned.

Query methods returning particular domain type collect the result from all result columns and nested structures in these (e.g. collected lists, maps etc..) and return as single Iterable<T>. Use Result Session.query(java.lang.String, java.util.Map<java.lang.String,?>) to retrieve only objects in particular column.

In the current version, custom queries do not support paging, sorting or a custom depth. In addition, it does not support mapping a path to domain entities, as such, a path should not be returned from a Cypher query. Instead, return nodes and relationships to have them mapped to domain entities.

Modifications made to the graph via Cypher queries directly will not be reflected in your domain objects within the session.

Sorting and paging

Neo4j-OGM supports Sorting and Paging of results when using the Session object. The Session object methods take independent arguments for Sorting and Pagination

Iterable<World> worlds = session.loadAll(World.class,
                                        new Pagination(pageNumber,itemsPerPage), depth)
Iterable<World> worlds = session.loadAll(World.class,
                                        new SortOrder().add("name"), depth)
Sort in descending order
Iterable<World> worlds = session.loadAll(World.class,
                                        new SortOrder().add(SortOrder.Direction.DESC,"name"))
Sorting with paging
Iterable<World> worlds = session.loadAll(World.class,
                                        new SortOrder().add("name"), new Pagination(pageNumber,itemsPerPage))

Neo4j-OGM does not yet support sorting and paging on custom queries.

10.8. Type Conversion

The object-graph mapping framework provides support for default and bespoke type conversions, which allow you to configure how certain data types are mapped to nodes or relationships in Neo4j. If you start with a new Neo4j project on Neo4j 3.4+, you should consider using the native type support of OGM for all temporal types.

10.8.1. Built-in type conversions

Neo4j-OGM will automatically perform the following type conversions:

  • Any object that extends java.lang.Number (including java.math.BigInteger and java.math.BigDecimal) to a String property

  • binary data (as byte[] or Byte[]) to base-64 String as Cypher does not support byte arrays

  • java.lang.Enum types using the enum’s name() method and Enum.valueOf()

  • java.util.Date to a String in the ISO 8601 format: "yyyy-MM-dd’T’HH:mm:ss.SSSXXX" (using DateString.ISO_8601)

  • java.time.Instant to a String in the ISO 8601 with timezone format: "yyyy-MM-dd’T’HH:mm:ss.SSSZ" (using DateTimeFormatter.ISO_INSTANT)

  • java.time.LocalDate to a String in the ISO 8601 with format: "yyyy-MM-dd" (using DateTimeFormatter.ISO_LOCAL_DATE)

  • java.time.LocalDateTime to a String in the ISO 8601 with format: "yyyy-MM-dd’T’HH:mm:ss" (using DateTimeFormatter.ISO_LOCAL_DATE_TIME)

  • java.time.OffsetDateTime to a String in the ISO 8601 with format: "YYYY-MM-dd’T’HH:mm:ss+01:00" / "YYYY-MM-dd’T’HH:mm:ss’Z'" (using DateTimeFormatter.ISO_OFFSET_DATE_TIME)

java.time.Instant based dates are stored in the database using UTC.

Two dedicated annotations are provided to modify the date conversion:

  1. @DateString

  2. @DateLong

They need to be applied to an attribute for a custom string format or in case you want to store a date or datetime value as long:

Example of user-defined date format
public class MyEntity {

    private Date entityDate;

Alternatively, if you want to store java.util.Date or java.time.Instant as long values, use the @DateLong annotation:

Example of date stored as a long value
public class MyEntity {

    private Date entityDate;

Collections of primitive or convertible values are also automatically mapped by converting them to arrays of their type or strings respectively.

Arrays are not supported for java.time.Instant, java.time.LocalDate, java.time.LocalDateTime, java.time.OffsetDateTime. Collections are not supported for java.time.Instant.
Lenient conversion

It is possible to explicitly assign the build-in converter annotations to the corresponding fields. This provides the advantage of being able to use the lenient attribute that will get be read by the converters. The supported annotations are @DateString, @EnumString and @NumberString. .Example of lenient converter usage

public class MyEntity {

    @DateString(lenient = true)
    private Date entityDate;

The lenient feature is currently only supported by string-based converters to allow the conversion of blank strings from the database.

10.8.2. Custom Type Conversion

In order to define bespoke type conversions for particular members, you can annotate a field with @Convert. One of either two convert implementations can be used. For simple cases where a single property maps to a single field, with type conversion, specify an implementation of AttributeConverter.

Example of mapping a single property to a field
public class MoneyConverter implements AttributeConverter<DecimalCurrencyAmount, Integer> {

   public Integer toGraphProperty(DecimalCurrencyAmount value) {
       return value.getFullUnits() * 100 + value.getSubUnits();

   public DecimalCurrencyAmount toEntityAttribute(Integer value) {
       return new DecimalCurrencyAmount(value / 100, value % 100);


You could then apply this to your class as follows:

public class Invoice {

   private DecimalCurrencyAmount value;

When more than one node property is to be mapped to a single field, use: CompositeAttributeConverter.

Example of mapping multiple node entity properties onto a single instance of a type
* This class maps latitude and longitude properties onto a Location type that encapsulates both of these attributes.
public class LocationConverter implements CompositeAttributeConverter<Location> {

    public Map<String, ?> toGraphProperties(Location location) {
        Map<String, Double> properties = new HashMap<>();
        if (location != null)  {
            properties.put("latitude", location.getLatitude());
            properties.put("longitude", location.getLongitude());
        return properties;

    public Location toEntityAttribute(Map<String, ?> map) {
        Double latitude = (Double) map.get("latitude");
        Double longitude = (Double) map.get("longitude");
        if (latitude != null && longitude != null) {
            return new Location(latitude, longitude);
        return null;


And just as with an AttributeConverter, a CompositeAttributeConverter could be applied to your class as follows:

public class Person {

   private Location location;

10.9. Filters

Filters provide a mechanism for customising the where clause of Cypher generated by Neo4j-OGM. They can be chained together with boolean operators, and associated with a comparison operator. Additionally, each filter contains a FilterFunction. A filter function can be provided when the filter is instantiated, otherwise, by default a PropertyComparison is used.

In the example below, we are return a collection containing any satellites that are manned.

Example of using a Filter
Collection<Satellite> satellites = session.loadAll(Satellite.class, new Filter("manned", ComparisonOperator.EQUALS, true));
Example of chained Filters
Filter mannedFilter = new Filter("manned", ComparisonOperator.EQUALS, true);
Filter landedFilter = new Filter("landed", ComparisonOperator.EQUALS, false);

Filters satelliteFilter = mannedFilter.and(landedFilter);
The filters should be considered as immutable. In previous versions, you could change filter values after instantiation, this is not the case anymore.

10.10. Events

Neo4j-OGM supports persistence events. This section describes how to intercept update and delete events.

You may also check the @PostLoad annotation which is described here.

10.10.1. Event types

There are four types of events:


Events are fired for every @NodeEntity or @RelationshipEntity object that is created, updated or deleted, or otherwise affected by a save or delete request. This includes:

  • The top-level objects or objects being created, modified or deleted.

  • Any connected objects that have been modified, created or deleted.

  • Any objects affected by the creation, modification or removal of a relationship in the graph.

Events will only fire when one of the session.save() or session.delete() methods is invoked. Directly executing Cypher queries against the database using session.query() will not trigger any events.

10.10.2. Interfaces

The events mechanism introduces two new interfaces, Event and EventListener.

The Event interface

The Event interface is implemented by PersistenceEvent. Whenever an application wishes to handle an event it will be given an instance of Event, which exposes the following methods:

public interface Event {

    Object getObject();
    LIFECYCLE getLifeCycle();

    enum LIFECYCLE {

The event listener interface

The EventListener interface provides methods allowing implementing classes to handle each of the different Event types:

public interface EventListener {

    void onPreSave(Event event);
    void onPostSave(Event event);
    void onPreDelete(Event event);
    void onPostDelete(Event event);


Although the Event interface allows you to retrieve the event type, in most cases, your code won’t need it because the EventListener provides methods to capture each type of event explicitly.

10.10.3. Registering an EventListener

There are two way to register an event listener:

  • on an individual Session

  • across multiple sessions by using a SessionFactory

In this example we register an anonymous EventListener to inject a UUID onto new objects before they’re saved

class AddUuidPreSaveEventListener implements EventListener {

    void onPreSave(Event event) {
        DomainEntity entity = (DomainEntity) event.getObject():
        if (entity.getId() == null) {
    void onPostSave(Event event) {
    void onPreDelete(Event event) {
    void onPostDelete(Event event) {

EventListener eventListener = new AddUuidPreSaveEventListener();

// register it on an individual session

// remove it.

// register it across multiple sessions

// remove it.

It is possible and sometimes desirable to add several EventListener objects to the session, depending on the application’s requirements. For example, our business logic might require us to add a UUID to a new object, as well as manage wider concerns such as ensuring that a particular persistence event won’t leave our domain model in a logically inconsistent state. It is usually a good idea to separate these concerns into different objects with specific responsibilities, rather than having one single object try to do everything.

10.10.4. Using the EventListenerAdapter

The EventListener above is fine, but we’ve had to create three methods for events we don’t intend to handle. It would be preferable if we didn’t have to do this each time we needed an EventListener.

The EventListenerAdapter is an abstract class providing a no-op implementation of the EventListener interface. If you don’t need to handle all the different types of persistence event you can create a subclass of EventListenerAdapter instead and override just the methods for the event types you’re interested in.

For example:

class PreSaveEventListener extends EventListenerAdapter {
    void onPreSave(Event event) {
        DomainEntity entity = (DomainEntity) event.getObject();
        if (entity.id == null) {
            entity.UUID = UUID.randomUUID();

10.10.5. Disposing of an EventListener

Something to bear in mind is that once an EventListener has been registered it will continue to respond to all persistence events. Sometimes you may want only to handle events for a short period of time, rather than for the duration of the entire session.

If you are done with an EventListener you can stop it from firing any more events by invoking session.dispose(…​), passing in the EventListener to be disposed of.

The process of collecting persistence events prior to dispatching them to any EventListeners adds a small performance overhead to the persistence layer. Consequently, Neo4j-OGM is configured to suppress the event collection phase if there are no EventListeners registered with the Session. Using dispose() when you’re finished with an EventListener is good practice!

To remove an event listener across multiple sessions use the deregister method on the SessionFactory.

10.10.6. Connected objects

As mentioned previously, events are not only fired for the top-level objects being saved but for all their connected objects as well.

Connected objects are any objects reachable in the domain model from the top-level object being saved. Connected objects can be many levels deep in the domain model graph.

In this way, the events mechanism allows us to capture events for objects that we didn’t explicitly save ourselves.

// initialise the graph
Folder folder = new Folder("folder");
Document a = new Document("a");
Document b = new Document("b");
folder.addDocuments(a, b);


// change the names of both documents and save one of them

// because `b` is reachable from `a` (via the common shared folder) they will both be persisted,
// with PRE_SAVE and POST_SAVE events being fired for each of them

10.10.7. Events and types

When we delete a type, all the nodes with a label corresponding to that type are deleted in the graph. The affected objects are not enumerated by the events mechanism (they may not even be known). Instead, _DELETE events will be raised for the type:

    // 2 events will be fired when the type is deleted.
    // - PRE_DELETE Document.class
    // - POST_DELETE Document.class

10.10.8. Events and collections

When saving or deleting a collection of objects, separate events are fired for each object in the collection, rather than for the collection itself.

Document a = new Document("a");
Document b = new Document("b");

// 4 events will be fired when the collection is saved.
// - PRE_SAVE a
// - PRE_SAVE b
// - POST_SAVE a
// - POST_SAVE b

session.save(Arrays.asList(a, b));

10.10.9. Event ordering

Events are partially ordered. PRE_ events are guaranteed to fire before any POST_ event within the same save or delete request. However, the internal ordering of the PRE_ events and POST_ events with the request is undefined.

Example: Partial ordering of events
Document a = new Document("a");
Document b = new Document("b");

// Although the save order of objects is implied by the request, the PRE_SAVE event for `b`
// may be fired before the PRE_SAVE event for `a`, and similarly for the POST_SAVE events.
// However, all PRE_SAVE events will be fired before any POST_SAVE event.

session.save(Arrays.asList(a, b));

10.10.10. Relationship events

The previous examples show how events fire when the underlying node representing an entity is updated or deleted in the graph. Events are also fired when a save or delete request results in the modification, addition or deletion of a relationship in the graph.

For example, if you delete a Document object that is contained in the documents collection of a Folder, events will be fired for the Document as well as the Folder, to reflect the fact that the relationship between the folder and the document has been removed in the graph.

Example: Deleting a Document attached to a Folder
Folder folder = new Folder();
Document a = new Document("a");

// When we delete the document, the following events will be fired
// - PRE_SAVE folder  (1)
// - POST_SAVE folder
1 Note that the folder events are _SAVE events, not _DELETE events. The folder was not deleted.

The event mechanism does not try to synchronise your domain model. In this example, the folder is still holding a reference to the Document, even though it no longer exists in the graph. As always, your code must take care of domain model synchronisation.

10.10.11. Event uniqueness

The event mechanism guarantees to not fire more than one event of the same type for an object in a save or delete request.

Example: Multiple changes, single event of each type
 // Even though we're making changes to both the folder node, and its relationships,
 // only one PRE_SAVE and one POST_SAVE event will be fired.

10.11. Testing

Doing integration testing with Neo4j-OGM requires a few basic steps :

  • Add the org.neo4j.test:neo4j-harness artifact to your Maven / Gradle configuration

  • Declare the Neo4jRule JUnit rule, to setup a Neo4j test server

  • Setup Neo4j-OGM configuration and SessionFactory

An example of a full running configuration can be found in the issue templates.

10.11.1. Log levels

When running unit tests, it can be useful to see what Neo4j-OGM is doing, and in particular to see the Cypher requests being transferred between your application and the database. Neo4j-OGM uses slf4j along with Logback as its logging framework and by default the log level for all Neo4j-OGM components is set to WARN, which does not include any Cypher output. To change Neo4j-OGM log level, create a file logback-test.xml in your test resources folder, configured as shown below:

<?xml version="1.0" encoding="UTF-8"?>

    <appender name="console" class="ch.qos.logback.core.ConsoleAppender">
            <pattern>%d %5p %40.40c:%4L - %m%n</pattern>

      ~ Set the required log level for Neo4j-OGM components here.
      ~ To just see Cypher statements set the level to "info"
      ~ For finer-grained diagnostics, set the level to "debug".
    <logger name="org.neo4j.ogm" level="info" />

    <root level="warn">
        <appender-ref ref="console" />


10.12. Clustering Support

The clustering features are only available in Neo4j Enterprise Edition.

Neo4j offers two separate solutions for ensuring redundancy and performance in a high-demand production environment:

  • Causal Clustering

  • Highly Available (HA) Cluster

Neo4j 3.1 introduced Causal Clustering – a brand-new architecture using the state-of-the-art Raft protocol – that enables support for ultra-large clusters and a wider range of cluster topologies for data center and cloud.

A Neo4j HA cluster is comprised of a single primary instance and zero or more secondary instances.

Please note that the HA technology is deprecated since Neo4j 3.4.

All instances in the cluster have full copies of the data in their local database files. The basic cluster configuration usually consists of three instances.

10.12.1. Causal Clustering

To find out more about Causal Clustering architecture please see the reference.

Causal Clustering only works with the Neo4j Bolt Driver (1.1.0 onwards). Trying to set this up with the HTTP or Embedded Driver will not work. The Bolt driver will fully handle any load balancing, which operate in concert with the Causal Cluster to spread the workload. New cluster-aware sessions, managed on the client-side by the Bolt drivers, alleviate complex infrastructure concerns for developers.

Configuring Neo4j-OGM

Not cluster specific side note: you may also want to configure connection testing.

To use clustering, simply configure your Bolt URI to use the bolt routing protocol:

URI=bolt+routing://instance0 (1)


URIS=bolt+routing://instance0 (1)
1 instance0 must be one of your core cluster group (that accepts reads and writes).
Design considerations for clustering

In this section we go through important points to be aware of when using causal clustering.

  • Review hardware and cluster configuration

  • Target replica servers when possible

  • Use bookmarks to read your own writes

  • Plan for failure

Cluster configuration

Please read the causal cluster reference to plan the best topology according to your needs.

You can provide additional core instances in URIS property, separated by a comma. The URI property is optional as long as all URIs are provided in the URIS property. Same credentials are used for all instances. Please keep in mind that all listed instances must be core servers.

Target replica servers when possible

By default all Session 's Transaction s are set to read/write. This means reads and writes will always hit the core cluster. To offload the core servers and improve performance, it is advised if possible to route traffic to the replica servers. This is done in the application code, by declaring sessions / transactions as read-only. You can call session.beginTransaction(Transaction.Type) with READ to do that.

This is not always possible. You may only do this if you can afford to read some slightly outdated data.
Use bookmarks to read your own writes

Causal consistency allows you to specify guarantees around query ordering, including the ability to read your own writes, view the last data you read, and later on, committed writes from other users. The Bolt drivers collaborate with the core servers to ensure that all transactions are applied in the same order using a concept of a bookmark.

The cluster returns a bookmark when it commits an update transaction, so then the driver links a bookmark to the user’s next transaction. The server that received query starts this new bookmarked transaction only when its internal state reached the desired bookmark. This ensures that the view of related data is always consistent, that all servers are eventually updated, and that users reading and re-reading data always see the same — and the latest — data.

If you have multiple application tier JVM instances you will need to manage this state across them. The Session object allows you to retrieve bookmarks through the use of Session.getLastBookmark() and start new transactions with given bookmark through Session.beginTransaction(type, bookmarks).

Do not generalize the use of bookmarks as they have impact on latency.
Retry mechanisms

The driver does its best to ensure a stable communication between the application tier and the database. It handles low level failures (like connection loss), but cannot do much about higher level failures (like cluster unavailability). However, due to the nature of distributed platforms, failures arise. When the cluster is split among several datacenters, network issues can cause cluster instability. Cluster members not being able to talk to each other can make the cluster, for example, fall in read only mode, or trigger leader re-election.

For critical applications, these failures have to be anticipated, and also managed at the architecture or application level. Even if the driver handles some low level retries, it is not always enough in case of instability, as an application may involve complex business logic, and require coarse grained units of work.

Solutions like application retries or message queuing are good candidates to handle this kind of scenario.

10.12.2. Highly Available (HA) Cluster

A typical Neo4j HA cluster will consist of a primary node and a couple of secondary nodes for providing failover capability and optionally for handling reads. (Although it is possible to write to secondary nodes, this is uncommon because it requires additional effort to synchronise a secondary node with the primary node node.)

Typical HA Cluster

Transaction binding in HA mode

When operating in HA mode, Neo4j does not make open transactions available across all nodes in the cluster. This means we must bind every request within a specific transaction to the same node in the cluster, or the commit will fail with 404 Not Found.

Read-only transactions

As of Version 2.0.5 read-only transactions are supported by Neo4j-OGM.


The Drivers have been updated to transmit additional information about the transaction type of the current transaction to the server.

  • The HTTP Driver implementation sets a HTTP Header "X-WRITE" to "1" for READ_WRITE transactions (the default) or to "0" for READ_ONLY ones.

  • The Embedded Driver can support both READ_ONLY and READ_WRITE (as of version 2.1.0).

  • The native Bolt Driver can support both READ_ONLY and READ_WRITE (as of version 2.1.0).

11. Appendix

Appendix A: Namespace reference

The <repositories /> Element

The <repositories /> element triggers the setup of the Spring Data repository infrastructure. The most important attribute is base-package, which defines the package to scan for Spring Data repository interfaces. See “XML Configuration”. The following table describes the attributes of the <repositories /> element:

Table 8. Attributes
Name Description


Defines the package to be scanned for repository interfaces that extend *Repository (the actual interface is determined by the specific Spring Data module) in auto-detection mode. All packages below the configured package are scanned, too. Wildcards are allowed.


Defines the postfix to autodetect custom repository implementations. Classes whose names end with the configured postfix are considered as candidates. Defaults to Impl.


Determines the strategy to be used to create finder queries. See “Query Lookup Strategies” for details. Defaults to create-if-not-found.


Defines the location to search for a Properties file containing externally defined queries.


Whether nested repository interface definitions should be considered. Defaults to false.

Appendix B: Populators namespace reference

The <populator /> element

The <populator /> element allows to populate the a data store via the Spring Data repository infrastructure.[1]

Table 9. Attributes
Name Description


Where to find the files to read the objects from the repository shall be populated with.

Appendix C: Repository query keywords

Supported query method subject keywords

The following table lists the subject keywords generally supported by the Spring Data repository query derivation mechanism to express the predicate. Consult the store-specific documentation for the exact list of supported keywords, because some keywords listed here might not be supported in a particular store.

Table 10. Query subject keywords
Keyword Description

find…By, read…By, get…By, query…By, search…By, stream…By

General query method returning typically the repository type, a Collection or Streamable subtype or a result wrapper such as Page, GeoResults or any other store-specific result wrapper. Can be used as findBy…, findMyDomainTypeBy… or in combination with additional keywords.


Exists projection, returning typically a boolean result.


Count projection returning a numeric result.

delete…By, remove…By

Delete query method returning either no result (void) or the delete count.

…First<number>…, …Top<number>…

Limit the query results to the first <number> of results. This keyword can occur in any place of the subject between find (and the other keywords) and by.


Use a distinct query to return only unique results. Consult the store-specific documentation whether that feature is supported. This keyword can occur in any place of the subject between find (and the other keywords) and by.

Supported query method predicate keywords and modifiers

The following table lists the predicate keywords generally supported by the Spring Data repository query derivation mechanism. However, consult the store-specific documentation for the exact list of supported keywords, because some keywords listed here might not be supported in a particular store.

Table 11. Query predicate keywords
Logical keyword Keyword expressions






After, IsAfter


Before, IsBefore


Containing, IsContaining, Contains


Between, IsBetween


EndingWith, IsEndingWith, EndsWith




False, IsFalse


GreaterThan, IsGreaterThan


GreaterThanEqual, IsGreaterThanEqual


In, IsIn


Is, Equals, (or no keyword)


IsEmpty, Empty


IsNotEmpty, NotEmpty


NotNull, IsNotNull


Null, IsNull


LessThan, IsLessThan


LessThanEqual, IsLessThanEqual


Like, IsLike


Near, IsNear


Not, IsNot


NotIn, IsNotIn


NotLike, IsNotLike


Regex, MatchesRegex, Matches


StartingWith, IsStartingWith, StartsWith


True, IsTrue


Within, IsWithin

In addition to filter predicates, the following list of modifiers is supported:

Table 12. Query predicate modifier keywords
Keyword Description

IgnoreCase, IgnoringCase

Used with a predicate keyword for case-insensitive comparison.

AllIgnoreCase, AllIgnoringCase

Ignore case for all suitable properties. Used somewhere in the query method predicate.


Specify a static sorting order followed by the property path and direction (e. g. OrderByFirstnameAscLastnameDesc).

Appendix D: Repository query return types

Supported Query Return Types

The following table lists the return types generally supported by Spring Data repositories. However, consult the store-specific documentation for the exact list of supported return types, because some types listed here might not be supported in a particular store.

Geospatial types (such as GeoResult, GeoResults, and GeoPage) are available only for data stores that support geospatial queries. Some store modules may define their own result wrapper types.
Table 13. Query return types
Return type Description


Denotes no return value.


Java primitives.

Wrapper types

Java wrapper types.


A unique entity. Expects the query method to return one result at most. If no result is found, null is returned. More than one result triggers an IncorrectResultSizeDataAccessException.


An Iterator.


A Collection.


A List.


A Java 8 or Guava Optional. Expects the query method to return one result at most. If no result is found, Optional.empty() or Optional.absent() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.


Either a Scala or Vavr Option type. Semantically the same behavior as Java 8’s Optional, described earlier.


A Java 8 Stream.


A convenience extension of Iterable that directy exposes methods to stream, map and filter results, concatenate them etc.

Types that implement Streamable and take a Streamable constructor or factory method argument

Types that expose a constructor or ….of(…)/….valueOf(…) factory method taking a Streamable as argument. See Returning Custom Streamable Wrapper Types for details.

Vavr Seq, List, Map, Set

Vavr collection types. See Support for Vavr Collections for details.


A Future. Expects a method to be annotated with @Async and requires Spring’s asynchronous method execution capability to be enabled.


A Java 8 CompletableFuture. Expects a method to be annotated with @Async and requires Spring’s asynchronous method execution capability to be enabled.


A org.springframework.util.concurrent.ListenableFuture. Expects a method to be annotated with @Async and requires Spring’s asynchronous method execution capability to be enabled.


A sized chunk of data with an indication of whether there is more data available. Requires a Pageable method parameter.


A Slice with additional information, such as the total number of results. Requires a Pageable method parameter.


A result entry with additional information, such as the distance to a reference location.


A list of GeoResult<T> with additional information, such as the average distance to a reference location.


A Page with GeoResult<T>, such as the average distance to a reference location.


A Project Reactor Mono emitting zero or one element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.


A Project Reactor Flux emitting zero, one, or many elements using reactive repositories. Queries returning Flux can emit also an infinite number of elements.


A RxJava Single emitting a single element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.


A RxJava Maybe emitting zero or one element using reactive repositories. Expects the query method to return one result at most. If no result is found, Mono.empty() is returned. More than one result triggers an IncorrectResultSizeDataAccessException.


A RxJava Flowable emitting zero, one, or many elements using reactive repositories. Queries returning Flowable can emit also an infinite number of elements.

Appendix E: Migration Guide

Migrating from 4.2 → 5.0/5.1

  • Base class for repositories GraphRepository has been renamed Neo4jRepository and parameter types change from <T> to <T, ID>.

  • All Repository methods can return Streams.

  • The repository method naming scheme has changed for SD commons 2.0 as part of DATACMNS-944.

    • for example, findOne repository methods are renamed findById and now return Optional<T>.

    • please check the JavaDoc of org.springframework.data.repository.CrudRepository

  • Paged custom queries no longer accept queries without countQuery attribute.

  • The keywords Between and IsBetween in query methods now include the given limits in the query. Use a combination of GreaterThan/isGreaterThan and LessThan/isLessThan (e.g. isGreaterThanLowerLimitAndIsLessThanUpperLimit) to keep the exclusive behavior.

  • Id handling : Long native ids are not mandatory anymore. See GraphId field.

  • Primary indexes are now deprecated and replaced by @Id See Entity identifier.

  • Annotations on accessors are no longer valid. See Annotating entities.

  • Loading with depth -1 calls have to be reviewed (please see the Neo4j-OGM migration guide under Migration from 2.1 to 3.0 / Performance and unlimited load depth).

  • The ogm.properties file and environment variable have been removed. You have to explicitly provide the configuration file now or configure the driver programmatically. See the configuration section.

  • The driver class name in the configuration is now inferred from connection URL.

  • Java 8 dates are now better supported ; the use of java.util.Date or converters is not required anymore. You may want to switch to more fine grained date types like Instant. See conversions.

  • The query filters are now immutable. See Filters.

Migrating from 4.0/4.1 → 4.2

Spring Data Neo4j 4.2 significantly reduces complexity of configuration for application developers. There is no longer a need to extend from Neo4jConfiguration or define a Session bean. Configuration for various types of applications are described here

  1. Remove any subclassing of Neo4jConfiguration

  2. Define the sessionFactory bean with an instance of SessionFactory and the transactionManager bean with an instance of Neo4jTransactionManager. Be sure to pass the SessionFactory into the constructor for the transaction manager.

Migrating from pre 4.0 → 4.2

Package Changes

Because the Neo4j Object Graph Mapper can be used independently of Spring Data Neo4j, the core annotations have been moved out of the spring framework packages:


The @Query and @QueryResult annotations are only supported in the Spring modules, and are not used by the core mapping framework. These annotations have not changed.

Annotation Changes

There have been some changes to the annotations that were used in previous versions of Spring Data Neo4j. Wherever possible we have tried to maintain the previous annotations verbatim, but in a few cases this has not been possible, usually for technical reasons but sometimes for aesthetic ones. Our goal has been to minimise the number of annotations you need to use as well as trying to make them more self-explanatory. The following annotations have been changed.













Relationship Direction.BOTH


Custom Type Conversion

SDN provides automatic type conversion for the obvious candidates: byte[] and Byte[] arrays, Dates, BigDecimal and BigInteger types. In order to define bespoke type conversions for particular entity attribute, you can annotate a field or method with @Convert to specify your own implementation of org.neo4j.ogm.typeconversion.AttributeConverter.

You can find out more about type conversions here: Custom Converters

Date Format Changes

The default Date converter is @DateString.

SDN 3.x and earlier represented Dates as a String value consisting of the number of milliseconds since January 1, 1970, 00:00:00 GMT.

If you are upgrading to SDN 4.x from these versions and your application used the default, then you need to annotate your Date properties with @DateLong. Moreover, the property values in the graph need to be converted to numbers.

Upgrade Date properties to numbers
MATCH (n:Foo) //All nodes which contain date properties to be migrated
WHERE NOT HAS(n.migrated)// Take the first 10k nodes that haven't been migrated yet
WITH n LIMIT 10000
SET n.dateProperty = toInt(n.dateProperty),n.migrated=1 //where dateProperty is the date with a String value to be migrated
RETURN count(n); //Run until the statement returns zero records
//Similar process to remove the migrated flag

However, if your application already represented Dates as @GraphProperty(propertyType = Long.class) then simply changing this to @DateLong is sufficient.


The best way to retrieve start nodes for traversals and queries is by using Neo4j’s integrated index facilities. SDN supports Index and Constraint management but differs in how it does this to previous versions.

Obsolete Annotations

The following annotations are no longer used, either because they are no longer needed, or cannot be supported via Cypher.

  • @GraphTraversal

  • @RelatedToVia

  • @RelatedTo

  • @TypeAlias

  • @Fetch

Features No Longer Supported

Some features of the previous annotations have been dropped.

Overriding @Property Types

Support for overriding property types via arguments to @Property has been dropped. If your attribute requires a non-default conversion to and from a database property, you can use a Custom Converter instead.

@Relationship enforceTargetType

In previous versions of Spring Data Neo4j, you would have to add an enforceTargetType attribute into every clashing @Relationship annotation. Thanks to changes in the underlying object-graph mapping mechanism, this is no longer necessary.

Clashing Relationship Types
class Person {
    private Car car;

    private Pet pet;
Cross-store Persistence

Neo4j is dropping XA support and therefore SDN does not provide any capability for cross-store persistence


SDN 4 replaces the existing TypeRepresentionStrategy configuration with a straightforward convention based on simple class-names or entities using @NodeEntity(label=…​)

AspectJ Support

Support for AspectJ-based persistence has been removed from SDN 4 as the write-and-read-through approach only works with an integrated, embedded database, not Neo4j server. The performance improvements in SDN 4 should make their use as a performance optimisation unnecessary anyway.

Deprecation of Neo4jTemplate

Users that rely on a direct interaction with the database should be using the Neo4j-OGM Session directly. Neo4jTemplate has been kept to give upgrading users a better experience.

The Neo4jTemplate has been slimmed-down significantly for SDN 4. It contains the exact same methods as Session. In fact Neo4jTemplate is just a very thin wrapper with an ability to support SDN Exception Translation. Many of the operations are no longer needed or can be expressed with a straightforward Cypher query.

If you do use Neo4jTemplate, then you should code against its Neo4jOperations interface instead of the template class.

The following table shows the Neo4jTemplate functions that have been retained for version 4 of Spring Data Neo4j. In some cases the method names have changed but the same functionality is offered under the new version.

Table 14. Neo4j Template Method Migration
Old Method Name New Method Name Notes



Overloaded to take optional depth parameter



Overloaded to take optional depth parameter, also now returns a Collection rather than a Result



Return type changed from Result to be Iterable







No longer defines generic type parameters



Indexes are not supported natively, but you can index node properties in your database setup and use this method to find by them

To achieve the old template.fetch(entity) equivalent behaviour, you should call one of the load methods specifying the fetch depth as a parameter.

It’s also worth noting that exec(GraphCallback) and the create…​() methods have been made obsolete by Cypher. Instead, you should now issue a Cypher query to the new execute method to create the nodes or relationships that you need.

Dynamic labels, properties and relationship types are not supported as of this version, server extensions should be considered instead.

Built-In Query DSL Support

Previous versions of SDN allowed you to use a DSL to generate Cypher queries. There are many different DSL libraries available and you’re free to use which of these - or none - that you want. With Cypher changing on a regular basis, avoiding a DSL implementation in SDN means less ongoing maintenance and less likelihood of your code being incompatible with future versions of Neo4j.

Graph Traversal and Node/Relationship Manipulation

These features cannot be supported by Cypher and have therefore been dropped from Neo4jTemplate.

Appendix F: Frequently asked questions

  1. What is the difference between Neo4j-OGM and Spring Data Neo4j (SDN)?

    Spring Data Neo4j (SDN) uses Neo4j-OGM to perform the mapping to and from the database. OGM can be seen on the same level as a JPA implementation like Hibernate in the context of Spring Data JPA.

  2. How do I set up my Spring Configuration with Spring WebMVC projects?

    If you are using a Spring WebMVC application, the following configuration is all that’s required:

    public class MyWebAppConfiguration extends WebMvcConfigurerAdapter {
        public SessionFactory sessionFactory() {
            // with domain entity base package(s)
            return new SessionFactory("org.neo4j.example.domain");
        public Neo4jTransactionManager transactionManager() throws Exception {
            return new Neo4jTransactionManager(sessionFactory());
  3. Do I need to setup an OpenSessionInViewFilter?

    It depends but in most cases the answer is no.

    First let’s recap what a so called OpenSessionInViewFilter does: As soon as a web request arrives at your application it will make sure, a write transaction is opened and every interaction with the Neo4j database will happen in that transaction.

    While this removes the need to think about transactional boundaries, it comes at a price: As the filter cannot know upfront whether you will only execute read queries or will execute writes. Therefore it will open a write transaction. In a cluster environment that will prevent load distribution among the read replicas, as they would not be able to answer writes.

    The general recommendation is to wrap a chain of calls to the Neo4j-OGM session or any repository inside a dedicated service like this:

    public class MyService {
        // If you need the session, it should be injected like that
        // The infrastructure will make sure it is always one that fits your transaction.
        // private final Session session;
        private final MyRepository myRepository;
        public MyService(MyRepository myRepository) {
            this.myRepository = myRepository;
        @Transactional (1)
        public void doSomething() {
            MyObject thing = userRepository.findByName("whatever");
    1 Call this method from your web controller instead of relying on the OSIV interceptor. Thus you have a clean transactional boundary at the service level.

    If you still want to have the interceptor, you can enable it on a Spring Boot application with spring.data.neo4j.open-in-view=true or in a plain Spring application with a configuration like that:

    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;
    import org.springframework.data.neo4j.web.support.OpenSessionInViewInterceptor;
    import org.springframework.web.servlet.config.annotation.InterceptorRegistry;
    import org.springframework.web.servlet.config.annotation.WebMvcConfigurer;
    public class MyWebAppConfiguration {
        public OpenSessionInViewInterceptor openSessionInViewInterceptor() {
            return new OpenSessionInViewInterceptor();
        WebMvcConfigurer osivMvcConfigurer(
            OpenSessionInViewInterceptor openSessionInViewInterceptor
        ) {
            return new WebMvcConfigurer() {
                public void addInterceptors(InterceptorRegistry registry) {
    There is one special case in which you do need an open-session-in-view interceptor and that is when you use Spring Data Neo4j with Spring Data Rest. In that case however you don’t have control over the transactional boundaries. The PUT request for example will be executed with at least two repository interactions originating at the request handler.
    Also, the configuration above or the Spring Boot property will not be enough to enable open-session-in-view. Instead you want to use a configuration as shown in Enable open-session-in-view for Spring Data Rest.
    Enable open-session-in-view for Spring Data Rest
    import org.springframework.context.annotation.Bean;
    import org.springframework.context.annotation.Configuration;
    import org.springframework.data.neo4j.web.support.OpenSessionInViewInterceptor;
    import org.springframework.web.servlet.handler.MappedInterceptor;
    public class MyWebAppConfigurationForSpringDataRest {
    	@Bean (1)
    	public OpenSessionInViewInterceptor openSessionInViewInterceptor() {
    		return new OpenSessionInViewInterceptor();
    	@Bean (2)
    	public MappedInterceptor mappedOSIVInterceptor(OpenSessionInViewInterceptor openSessionInViewInterceptor) {
    		return new MappedInterceptor(new String[] { "/**" }, openSessionInViewInterceptor);
    1 You don’t need this bean if you already have the open-session-in-view interceptor, either through the Spring Boot property or manual configuration.
    2 This MappedInterceptor is required to enable open-session-in-view for Spring Data Rest.
  4. How do I set up my Spring Configuration with a Java Servlet 3.x+ Container project?

    If you are using a Java Servlet 3.x+ Container, you can configure a Servlet filter with Spring’s AbstractAnnotationConfigDispatcherServletInitializer like this:

    public class MyAppInitializer extends AbstractAnnotationConfigDispatcherServletInitializer {
      protected void customizeRegistration(ServletRegistration.Dynamic registration) {
          registration.setInitParameter("throwExceptionIfNoHandlerFound", "true");
      protected Class<?>[] getRootConfigClasses() {
          return new Class[] {ApplicationConfiguration.class} // if you have broken up your configuration, this points to your non web application config/s.
      protected Class<?>[] getServletConfigClasses() {
          throw new Class[] {WebConfiguration.class}; // a configuration that extends the WebMvcConfigurerAdapter as seen above.
      protected String[] getServletMappings() {
        return new String[] {"/"};

1. see XML Configuration