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This reference documentation describes the general usage of the Spring Data Couchbase library.

Migrating from Spring Data Couchbase 3.x to 4.x

This chapter is a quick reference of what major changes have been introduced in 4.x and gives a high-level overview of things to consider when migrating.

Please note that implicitly the minimum Couchbase Server version has been bumped up to 5.5 and later, and we recommend running at least 6.0.x.


Since the main objective was to migrate from the Java SDK 2 to 3, configuration has changed to adapt to the new SDK and also in the long run to prepare it for scopes and collections (but it can still be used without collection support).

XML Configuration support has been dropped, so only java/annotation based configuration is supported.

Your configuration still has to extend the AbstractCouchbaseConfiguration, but since RBAC (role-based access control) is now mandatory, different properties need to be overridden in order to be configured: getConnectionString, getUserName, getPassword and getBucketName. If you want to use a non-default scope optionally you can override the getScopeName method. Note that if you want to use certificate based authentication or you need to customize the password authentication, the authenticator method can be overridden to perform this task.

The new SDK still has an environment that is used to configure it, so you can override the configureEnvironment method and supply custom configuration if needed.

For more information, see Installation & Configuration.

Spring Boot Version Compatibility

Spring Boot 2.3.x or higher depends on Spring Data Couchbase 4.x. Earlier versions of Couchbase are not available because SDK 2 and 3 cannot live on the same classpath.


How to deal with entities has not changed, although since the SDK now does not ship annotations anymore only Spring-Data related annotations are supported.


  • com.couchbase.client.java.repository.annotation.Id became import org.springframework.data.annotation.Id

  • com.couchbase.client.java.repository.annotation.Field became import org.springframework.data.couchbase.core.mapping.Field

The org.springframework.data.couchbase.core.mapping.Document annotation stayed the same.

For more information, see Modeling Entities.

Automatic Index Management

Automatic Index Management has been redesigned to allow more flexible indexing. New annotations have been introduced and old ones like @ViewIndexed, @N1qlSecondaryIndexed and @N1qlPrimaryIndexed were removed.

For more information, see Automatic Index Management.

Template and ReactiveTemplate

Since the Couchbase SDK 3 removes support for RxJava and instead adds support for Reactor, both the couchbaseTemplate as well as the reactiveCouchbaseTemplate can be directly accessed from the AbstractCouchbaseConfiguration.

The template has been completely overhauled so that it now uses a fluent API to configure instead of many method overloads. This has the advantage that in the future we are able to extend the functionality without having to introduce more and more overloads that make it complicated to navigate.

The following table describes the method names in 3.x and compares them to their 4.x equivalents:

Table 1. Template Method Comparison
SDC 3.x SDC 4.x


















(call SDK directly)






(call SDK directly)

In addition, the following methods have been added which were not available in 3.x:

Table 2. Template Additions in 4.x
Name Description


Allows to remove entities through a N1QL query


Performs a find through the analytics service


Like findById, but takes replicas into account

We tried to unify and align the APIs more closely to the underlying SDK semantics so they are easier to correlate and navigate.

For more information, see Template & direct operations.

Repositories & Queries

  • org.springframework.data.couchbase.core.query.Query became org.springframework.data.couchbase.repository.Query

  • org.springframework.data.couchbase.repository.ReactiveCouchbaseSortingRepository has been removed. Consider extending ReactiveSortingRepository or ReactiveCouchbaseRepository

  • org.springframework.data.couchbase.repository.CouchbasePagingAndSortingRepository has been removed. Consider extending PagingAndSortingRepository or CouchbaseRepository

Support for views has been removed and N1QL queries are now the first-class citizens for all custom repository methods as well as the built-in ones by default.

The behavior itself has not changed over the previous version on how the query derivation is supposed to work. Should you encounter any queries that worked in the past and now do not work anymore please let us know.

It is possible to override the default scan consistency for N1QL queries through the new ScanConsistency annotation.

The method getCouchbaseOperations() has also been removed. You can still access all methods from the native Java SDK via the class CouchbaseTemplate or Cluster:

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.couchbase.core.CouchbaseTemplate;
import org.springframework.stereotype.Service;
import com.couchbase.client.java.Cluster;

public class MyService {

    private CouchbaseTemplate couchbaseTemplate;

    private Cluster cluster;

See Couchbase repositories for more information.

Full Text Search (FTS)

The FTS API has been simplified and now can be accessed via the Cluster class:

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
import com.couchbase.client.java.Cluster;
import com.couchbase.client.java.search.result.SearchResult;
import com.couchbase.client.java.search.result.SearchRow;
import com.couchbase.client.core.error.CouchbaseException;

public class MyService {

    private Cluster cluster;

    public void myMethod() {
        try {
          final SearchResult result = cluster
            .searchQuery("index", SearchQuery.queryString("query"));

          for (SearchRow row : result.rows()) {
            System.out.println("Found row: " + row);

          System.out.println("Reported total rows: "
            + result.metaData().metrics().totalRows());
        } catch (CouchbaseException ex) {

See the FTS Documentation for more information.

1. Upgrading Spring Data

Instructions for how to upgrade from earlier versions of Spring Data are provided on the project wiki. Follow the links in the release notes section to find the version that you want to upgrade to.

Upgrading instructions are always the first item in the release notes. If you are more than one release behind, please make sure that you also review the release notes of the versions that you jumped.

Reference Documentation

2. Installation & Configuration

This chapter describes the common installation and configuration steps needed when working with the library.

2.1. Installation

All versions intended for production use are distributed across Maven Central and the Spring release repository. As a result, the library can be included like any other maven dependency:

2.2. Configuration

Example 1. Including the dependency through maven

This will pull in several dependencies, including the underlying Couchbase Java SDK, common Spring dependencies and also Jackson as the JSON mapping infrastructure.

You can also grab snapshots from the spring snapshot repository ( https://repo.spring.io/snapshot ) and milestone releases from the spring milestone repository ( https://repo.spring.io/milestone ). Here is an example on how to use the current SNAPSHOT dependency:

2.3. Snapshot Configuration

Example 2. Using a snapshot version

  <name>Spring Snapshot Repository</name>

2.4. Overriding the Couchbase SDK Version

Some users may wish to use a Couchbase Java SDK version different from the one referenced in a Spring Data Couchbase release for the purpose of obtaining bug and vulnerability fixes. Since Couchbase Java SDK minor version releases are backwards compatible, this version of Spring Data Couchbase is compatible and supported with any 3.x version of the Couchbase Java SDK newer than the one specified in the release dependencies. To change the Couchbase Java SDK version used by Spring Data Couchbase, simply override the dependency in the application pom.xml as follows:

Example 3. If Using the spring-data-couchbase Dependency Directly
  <exclusions> <!-- exclude Couchbase Java SDK -->

<dependency> <!-- add dependency for specific Couchbase Java SDK version -->
Example 4. If Using the spring-data-starter-couchbase Dependency (from Spring Initialzr)

  <exclusions> <!-- exclude Couchbase Java SDK -->

<dependency> <!-- add dependency for specific Couchbase Java SDK version -->

Once you have all needed dependencies on the classpath, you can start configuring it. Only Java config is supported (XML config has been removed in 4.0).

2.5. Annotation-based Configuration ("JavaConfig")

To get started, all you need to do is subclcass the AbstractCouchbaseConfiguration and implement the abstract methods.

Example 5. Extending the AbstractCouchbaseConfiguration
public class Config extends AbstractCouchbaseConfiguration {

    public String getConnectionString() {
        return "couchbase://";

    public String getUserName() {
        return "Administrator";

    public String getPassword() {
        return "password";

    public String getBucketName() {
        return "travel-sample";

The connection string is made up of a list of hosts and an optional scheme (couchbase://) as shown in the code above. All you need to provide is a list of Couchbase nodes to bootstrap into (separated by a ,). Please note that while one host is sufficient in development, it is recommended to add 3 to 5 bootstrap nodes here. Couchbase will pick up all nodes from the cluster automatically, but it could be the case that the only node you’ve provided is experiencing issues while you are starting the application.

The userName and password are configured in your Couchbase Server cluster through RBAC (role-based access control). The bucketName reflects the bucket you want to use for this configuration.

Additionally, the SDK environment can be tuned by overriding the configureEnvironment method which takes a ClusterEnvironment.Builder to return a configured ClusterEnvironment.

Many more things can be customized and overridden as custom beans from this configuration (for example repositories, validation and custom converters).

If you use SyncGateway and CouchbaseMobile, you may run into problem with fields prefixed by _. Since Spring Data Couchbase by default stores the type information as a _class attribute this can be problematic. Override typeKey() (for example to return MappingCouchbaseConverter.TYPEKEY_SYNCGATEWAY_COMPATIBLE) to change the name of said attribute.

If you start your application, you should see Couchbase INFO level logging in the logs, indicating that the underlying Couchbase Java SDK is connecting to the database. If any errors are reported, make sure that the given credentials and host information are correct.

2.6. Configuring Multiple Buckets

To leverage multi-bucket repositories, implement the methods below in your Config class. The config*OperationsMapping methods configure the mapping of entity-objects to buckets. Be careful with the method names - using a method name that is a Bean will result in the value of that bean being used instead of the result of the method.

This example maps Person → protected, User → mybucket, and everything else goes to getBucketName(). Note that this only maps calls through the Repository.

public void configureReactiveRepositoryOperationsMapping(ReactiveRepositoryOperationsMapping baseMapping) {
 try {
  ReactiveCouchbaseTemplate personTemplate = myReactiveCouchbaseTemplate(myCouchbaseClientFactory("protected"),new MappingCouchbaseConverter());
  baseMapping.mapEntity(Person.class,  personTemplate); // Person goes in "protected" bucket
  ReactiveCouchbaseTemplate userTemplate = myReactiveCouchbaseTemplate(myCouchbaseClientFactory("mybucket"),new MappingCouchbaseConverter());
  baseMapping.mapEntity(User.class,  userTemplate); // User goes in "mybucket"
  // everything else goes in getBucketName()
 } catch (Exception e) {
  throw e;
public void configureRepositoryOperationsMapping(RepositoryOperationsMapping baseMapping) {
 try {
  CouchbaseTemplate personTemplate = myCouchbaseTemplate(myCouchbaseClientFactory("protected"),new MappingCouchbaseConverter());
  baseMapping.mapEntity(Person.class,  personTemplate); // Person goes in "protected" bucket
  CouchbaseTemplate userTemplate = myCouchbaseTemplate(myCouchbaseClientFactory("mybucket"),new MappingCouchbaseConverter());
  baseMapping.mapEntity(User.class,  userTemplate); // User goes in "mybucket"
  // everything else goes in getBucketName()
 } catch (Exception e) {
  throw e;

// do not use reactiveCouchbaseTemplate for the name of this method, otherwise the value of that bean
// will be used instead of the result of this call (the client factory arg is different)
public ReactiveCouchbaseTemplate myReactiveCouchbaseTemplate(CouchbaseClientFactory couchbaseClientFactory,
  MappingCouchbaseConverter mappingCouchbaseConverter) {
 return new ReactiveCouchbaseTemplate(couchbaseClientFactory, mappingCouchbaseConverter);

// do not use couchbaseTemplate for the name of this method, otherwise the value of that been
// will be used instead of the result from this call (the client factory arg is different)
public CouchbaseTemplate myCouchbaseTemplate(CouchbaseClientFactory couchbaseClientFactory,
  MappingCouchbaseConverter mappingCouchbaseConverter) {
 return new CouchbaseTemplate(couchbaseClientFactory, mappingCouchbaseConverter);

// do not use couchbaseClientFactory for the name of this method, otherwise the value of that bean will
// will be used instead of this call being made ( bucketname is an arg here, instead of using bucketName() )
public CouchbaseClientFactory myCouchbaseClientFactory(String bucketName) {
 return new SimpleCouchbaseClientFactory(getConnectionString(),authenticator(), bucketName );

3. Modeling Entities

This chapter describes how to model Entities and explains their counterpart representation in Couchbase Server itself.

3.1. Object Mapping Fundamentals

This section covers the fundamentals of Spring Data object mapping, object creation, field and property access, mutability and immutability. Note, that this section only applies to Spring Data modules that do not use the object mapping of the underlying data store (like JPA). Also be sure to consult the store-specific sections for store-specific object mapping, like indexes, customizing column or field names or the like.

Core responsibility of the Spring Data object mapping is to create instances of domain objects and map the store-native data structures onto those. This means we need two fundamental steps:

  1. Instance creation by using one of the constructors exposed.

  2. Instance population to materialize all exposed properties.

3.1.1. Object creation

Spring Data automatically tries to detect a persistent entity’s constructor to be used to materialize objects of that type. The resolution algorithm works as follows:

  1. If there is a single static factory method annotated with @PersistenceCreator then it is used.

  2. If there is a single constructor, it is used.

  3. If there are multiple constructors and exactly one is annotated with @PersistenceCreator, it is used.

  4. If the type is a Java Record the canonical constructor is used.

  5. If there’s a no-argument constructor, it is used. Other constructors will be ignored.

The value resolution assumes constructor/factory method argument names to match the property names of the entity, i.e. the resolution will be performed as if the property was to be populated, including all customizations in mapping (different datastore column or field name etc.). This also requires either parameter names information available in the class file or an @ConstructorProperties annotation being present on the constructor.

The value resolution can be customized by using Spring Framework’s @Value value annotation using a store-specific SpEL expression. Please consult the section on store specific mappings for further details.

Object creation internals

To avoid the overhead of reflection, Spring Data object creation uses a factory class generated at runtime by default, which will call the domain classes constructor directly. I.e. for this example type:

class Person {
  Person(String firstname, String lastname) { … }

we will create a factory class semantically equivalent to this one at runtime:

class PersonObjectInstantiator implements ObjectInstantiator {

  Object newInstance(Object... args) {
    return new Person((String) args[0], (String) args[1]);

This gives us a roundabout 10% performance boost over reflection. For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:

  • it must not be a private class

  • it must not be a non-static inner class

  • it must not be a CGLib proxy class

  • the constructor to be used by Spring Data must not be private

If any of these criteria match, Spring Data will fall back to entity instantiation via reflection.

3.1.2. Property population

Once an instance of the entity has been created, Spring Data populates all remaining persistent properties of that class. Unless already populated by the entity’s constructor (i.e. consumed through its constructor argument list), the identifier property will be populated first to allow the resolution of cyclic object references. After that, all non-transient properties that have not already been populated by the constructor are set on the entity instance. For that we use the following algorithm:

  1. If the property is immutable but exposes a with… method (see below), we use the with… method to create a new entity instance with the new property value.

  2. If property access (i.e. access through getters and setters) is defined, we’re invoking the setter method.

  3. If the property is mutable we set the field directly.

  4. If the property is immutable we’re using the constructor to be used by persistence operations (see Object creation) to create a copy of the instance.

  5. By default, we set the field value directly.

Property population internals

Similarly to our optimizations in object construction we also use Spring Data runtime generated accessor classes to interact with the entity instance.

class Person {

  private final Long id;
  private String firstname;
  private @AccessType(Type.PROPERTY) String lastname;

  Person() {
    this.id = null;

  Person(Long id, String firstname, String lastname) {
    // Field assignments

  Person withId(Long id) {
    return new Person(id, this.firstname, this.lastame);

  void setLastname(String lastname) {
    this.lastname = lastname;
Example 6. A generated Property Accessor
class PersonPropertyAccessor implements PersistentPropertyAccessor {

  private static final MethodHandle firstname;              (2)

  private Person person;                                    (1)

  public void setProperty(PersistentProperty property, Object value) {

    String name = property.getName();

    if ("firstname".equals(name)) {
      firstname.invoke(person, (String) value);             (2)
    } else if ("id".equals(name)) {
      this.person = person.withId((Long) value);            (3)
    } else if ("lastname".equals(name)) {
      this.person.setLastname((String) value);              (4)
1 PropertyAccessor’s hold a mutable instance of the underlying object. This is, to enable mutations of otherwise immutable properties.
2 By default, Spring Data uses field-access to read and write property values. As per visibility rules of private fields, MethodHandles are used to interact with fields.
3 The class exposes a withId(…) method that’s used to set the identifier, e.g. when an instance is inserted into the datastore and an identifier has been generated. Calling withId(…) creates a new Person object. All subsequent mutations will take place in the new instance leaving the previous untouched.
4 Using property-access allows direct method invocations without using MethodHandles.

This gives us a roundabout 25% performance boost over reflection. For the domain class to be eligible for such optimization, it needs to adhere to a set of constraints:

  • Types must not reside in the default or under the java package.

  • Types and their constructors must be public

  • Types that are inner classes must be static.

  • The used Java Runtime must allow for declaring classes in the originating ClassLoader. Java 9 and newer impose certain limitations.

By default, Spring Data attempts to use generated property accessors and falls back to reflection-based ones if a limitation is detected.

Let’s have a look at the following entity:

Example 7. A sample entity
class Person {

  private final @Id Long id;                                                (1)
  private final String firstname, lastname;                                 (2)
  private final LocalDate birthday;
  private final int age;                                                    (3)

  private String comment;                                                   (4)
  private @AccessType(Type.PROPERTY) String remarks;                        (5)

  static Person of(String firstname, String lastname, LocalDate birthday) { (6)

    return new Person(null, firstname, lastname, birthday,
      Period.between(birthday, LocalDate.now()).getYears());

  Person(Long id, String firstname, String lastname, LocalDate birthday, int age) { (6)

    this.id = id;
    this.firstname = firstname;
    this.lastname = lastname;
    this.birthday = birthday;
    this.age = age;

  Person withId(Long id) {                                                  (1)
    return new Person(id, this.firstname, this.lastname, this.birthday, this.age);

  void setRemarks(String remarks) {                                         (5)
    this.remarks = remarks;
1 The identifier property is final but set to null in the constructor. The class exposes a withId(…) method that’s used to set the identifier, e.g. when an instance is inserted into the datastore and an identifier has been generated. The original Person instance stays unchanged as a new one is created. The same pattern is usually applied for other properties that are store managed but might have to be changed for persistence operations. The wither method is optional as the persistence constructor (see 6) is effectively a copy constructor and setting the property will be translated into creating a fresh instance with the new identifier value applied.
2 The firstname and lastname properties are ordinary immutable properties potentially exposed through getters.
3 The age property is an immutable but derived one from the birthday property. With the design shown, the database value will trump the defaulting as Spring Data uses the only declared constructor. Even if the intent is that the calculation should be preferred, it’s important that this constructor also takes age as parameter (to potentially ignore it) as otherwise the property population step will attempt to set the age field and fail due to it being immutable and no with… method being present.
4 The comment property is mutable and is populated by setting its field directly.
5 The remarks property is mutable and is populated by invoking the setter method.
6 The class exposes a factory method and a constructor for object creation. The core idea here is to use factory methods instead of additional constructors to avoid the need for constructor disambiguation through @PersistenceCreator. Instead, defaulting of properties is handled within the factory method. If you want Spring Data to use the factory method for object instantiation, annotate it with @PersistenceCreator.

3.1.3. General recommendations

  • Try to stick to immutable objects — Immutable objects are straightforward to create as materializing an object is then a matter of calling its constructor only. Also, this avoids your domain objects to be littered with setter methods that allow client code to manipulate the objects state. If you need those, prefer to make them package protected so that they can only be invoked by a limited amount of co-located types. Constructor-only materialization is up to 30% faster than properties population.

  • Provide an all-args constructor — Even if you cannot or don’t want to model your entities as immutable values, there’s still value in providing a constructor that takes all properties of the entity as arguments, including the mutable ones, as this allows the object mapping to skip the property population for optimal performance.

  • Use factory methods instead of overloaded constructors to avoid @PersistenceCreator — With an all-argument constructor needed for optimal performance, we usually want to expose more application use case specific constructors that omit things like auto-generated identifiers etc. It’s an established pattern to rather use static factory methods to expose these variants of the all-args constructor.

  • Make sure you adhere to the constraints that allow the generated instantiator and property accessor classes to be used — 

  • For identifiers to be generated, still use a final field in combination with an all-arguments persistence constructor (preferred) or a with… method — 

  • Use Lombok to avoid boilerplate code — As persistence operations usually require a constructor taking all arguments, their declaration becomes a tedious repetition of boilerplate parameter to field assignments that can best be avoided by using Lombok’s @AllArgsConstructor.

Overriding Properties

Java’s allows a flexible design of domain classes where a subclass could define a property that is already declared with the same name in its superclass. Consider the following example:

public class SuperType {

   private CharSequence field;

   public SuperType(CharSequence field) {
      this.field = field;

   public CharSequence getField() {
      return this.field;

   public void setField(CharSequence field) {
      this.field = field;

public class SubType extends SuperType {

   private String field;

   public SubType(String field) {
      this.field = field;

   public String getField() {
      return this.field;

   public void setField(String field) {
      this.field = field;

      // optional

Both classes define a field using assignable types. SubType however shadows SuperType.field. Depending on the class design, using the constructor could be the only default approach to set SuperType.field. Alternatively, calling super.setField(…) in the setter could set the field in SuperType. All these mechanisms create conflicts to some degree because the properties share the same name yet might represent two distinct values. Spring Data skips super-type properties if types are not assignable. That is, the type of the overridden property must be assignable to its super-type property type to be registered as override, otherwise the super-type property is considered transient. We generally recommend using distinct property names.

Spring Data modules generally support overridden properties holding different values. From a programming model perspective there are a few things to consider:

  1. Which property should be persisted (default to all declared properties)? You can exclude properties by annotating these with @Transient.

  2. How to represent properties in your data store? Using the same field/column name for different values typically leads to corrupt data so you should annotate least one of the properties using an explicit field/column name.

  3. Using @AccessType(PROPERTY) cannot be used as the super-property cannot be generally set without making any further assumptions of the setter implementation.

3.1.4. Kotlin support

Spring Data adapts specifics of Kotlin to allow object creation and mutation.

Kotlin object creation

Kotlin classes are supported to be instantiated, all classes are immutable by default and require explicit property declarations to define mutable properties.

Spring Data automatically tries to detect a persistent entity’s constructor to be used to materialize objects of that type. The resolution algorithm works as follows:

  1. If there is a constructor that is annotated with @PersistenceCreator, it is used.

  2. If the type is a Kotlin data cass the primary constructor is used.

  3. If there is a single static factory method annotated with @PersistenceCreator then it is used.

  4. If there is a single constructor, it is used.

  5. If there are multiple constructors and exactly one is annotated with @PersistenceCreator, it is used.

  6. If the type is a Java Record the canonical constructor is used.

  7. If there’s a no-argument constructor, it is used. Other constructors will be ignored.

Consider the following data class Person:

data class Person(val id: String, val name: String)

The class above compiles to a typical class with an explicit constructor.We can customize this class by adding another constructor and annotate it with @PersistenceCreator to indicate a constructor preference:

data class Person(var id: String, val name: String) {

    constructor(id: String) : this(id, "unknown")

Kotlin supports parameter optionality by allowing default values to be used if a parameter is not provided. When Spring Data detects a constructor with parameter defaulting, then it leaves these parameters absent if the data store does not provide a value (or simply returns null) so Kotlin can apply parameter defaulting.Consider the following class that applies parameter defaulting for name

data class Person(var id: String, val name: String = "unknown")

Every time the name parameter is either not part of the result or its value is null, then the name defaults to unknown.

Property population of Kotlin data classes

In Kotlin, all classes are immutable by default and require explicit property declarations to define mutable properties. Consider the following data class Person:

data class Person(val id: String, val name: String)

This class is effectively immutable. It allows creating new instances as Kotlin generates a copy(…) method that creates new object instances copying all property values from the existing object and applying property values provided as arguments to the method.

Kotlin Overriding Properties

Kotlin allows declaring property overrides to alter properties in subclasses.

open class SuperType(open var field: Int)

class SubType(override var field: Int = 1) :
	SuperType(field) {

Such an arrangement renders two properties with the name field. Kotlin generates property accessors (getters and setters) for each property in each class. Effectively, the code looks like as follows:

public class SuperType {

   private int field;

   public SuperType(int field) {
      this.field = field;

   public int getField() {
      return this.field;

   public void setField(int field) {
      this.field = field;

public final class SubType extends SuperType {

   private int field;

   public SubType(int field) {
      this.field = field;

   public int getField() {
      return this.field;

   public void setField(int field) {
      this.field = field;

Getters and setters on SubType set only SubType.field and not SuperType.field. In such an arrangement, using the constructor is the only default approach to set SuperType.field. Adding a method to SubType to set SuperType.field via this.SuperType.field = … is possible but falls outside of supported conventions. Property overrides create conflicts to some degree because the properties share the same name yet might represent two distinct values. We generally recommend using distinct property names.

Spring Data modules generally support overridden properties holding different values. From a programming model perspective there are a few things to consider:

  1. Which property should be persisted (default to all declared properties)? You can exclude properties by annotating these with @Transient.

  2. How to represent properties in your data store? Using the same field/column name for different values typically leads to corrupt data so you should annotate least one of the properties using an explicit field/column name.

  3. Using @AccessType(PROPERTY) cannot be used as the super-property cannot be set.

3.2. Documents and Fields

All entities should be annotated with the @Document annotation, but it is not a requirement.

Also, every field in the entity should be annotated with the @Field annotation. While this is - strictly speaking - optional, it helps to reduce edge cases and clearly shows the intent and design of the entity. It can also be used to store the field under a different name.

There is also a special @Id annotation which needs to be always in place. Best practice is to also name the property id.

Here is a very simple User entity:

Example 8. A simple Document with Fields
import org.springframework.data.annotation.Id;
import org.springframework.data.couchbase.core.mapping.Field;
import org.springframework.data.couchbase.core.mapping.Document;

public class User {

    private String id;

    private String firstname;

    private String lastname;

    public User(String id, String firstname, String lastname) {
        this.id = id;
        this.firstname = firstname;
        this.lastname = lastname;

    public String getId() {
        return id;

    public String getFirstname() {
        return firstname;

    public String getLastname() {
        return lastname;

Couchbase Server supports automatic expiration for documents. The library implements support for it through the @Document annotation. You can set a expiry value which translates to the number of seconds until the document gets removed automatically. If you want to make it expire in 10 seconds after mutation, set it like @Document(expiry = 10). Alternatively, you can configure the expiry using Spring’s property support and the expiryExpression parameter, to allow for dynamically changing the expiry value. For example: @Document(expiryExpression = "${valid.document.expiry}"). The property must be resolvable to an int value and the two approaches cannot be mixed.

If you want a different representation of the field name inside the document in contrast to the field name used in your entity, you can set a different name on the @Field annotation. For example if you want to keep your documents small you can set the firstname field to @Field("fname"). In the JSON document, you’ll see {"fname": ".."} instead of {"firstname": ".."}.

The @Id annotation needs to be present because every document in Couchbase needs a unique key. This key needs to be any string with a length of maximum 250 characters. Feel free to use whatever fits your use case, be it a UUID, an email address or anything else.

Writes to Couchbase-Server buckets can optionally be assigned durability requirements; which instruct Couchbase Server to update the specified document on multiple nodes in memory and/or disk locations across the cluster; before considering the write to be committed. Default durability requirements can also be configured through the @Document or @Durability annotations. For example: @Document(durabilityLevel = DurabilityLevel.MAJORITY) will force mutations to be replicated to a majority of the Data Service nodes. Both of the annotations support expression based durability level assignment via durabilityExpression attribute (Note SPEL is not supported).

3.3. Datatypes and Converters

The storage format of choice is JSON. It is great, but like many data representations it allows less datatypes than you could express in Java directly. Therefore, for all non-primitive types some form of conversion to and from supported types needs to happen.

For the following entity field types, you don’t need to add special handling:

Table 3. Primitive Types
Java Type JSON Representation


















Ignored on write

Since JSON supports objects ("maps") and lists, Map and List types can be converted naturally. If they only contain primitive field types from the last paragraph, you don’t need to add special handling too. Here is an example:

Example 9. A Document with Map and List
public class User {

    private String id;

    private List<String> firstnames;

    private Map<String, Integer> childrenAges;

    public User(String id, List<String> firstnames, Map<String, Integer> childrenAges) {
        this.id = id;
        this.firstnames = firstnames;
        this.childrenAges = childrenAges;


Storing a user with some sample data could look like this as a JSON representation:

Example 10. A Document with Map and List - JSON
    "_class": "foo.User",
    "childrenAges": {
        "Alice": 10,
        "Bob": 5
    "firstnames": [

You don’t need to break everything down to primitive types and Lists/Maps all the time. Of course, you can also compose other objects out of those primitive values. Let’s modify the last example so that we want to store a List of Children:

Example 11. A Document with composed objects
public class User {

    private String id;

    private List<String> firstnames;

    private List<Child> children;

    public User(String id, List<String> firstnames, List<Child> children) {
        this.id = id;
        this.firstnames = firstnames;
        this.children = children;

    static class Child {
        private String name;
        private int age;

        Child(String name, int age) {
            this.name = name;
            this.age = age;



A populated object can look like:

Example 12. A Document with composed objects - JSON
  "_class": "foo.User",
  "children": [
      "age": 4,
      "name": "Alice"
      "age": 3,
      "name": "Bob"
  "firstnames": [

Most of the time, you also need to store a temporal value like a Date. Since it can’t be stored directly in JSON, a conversion needs to happen. The library implements default converters for Date, Calendar and JodaTime types (if on the classpath). All of those are represented by default in the document as a unix timestamp (number). You can always override the default behavior with custom converters as shown later. Here is an example:

Example 13. A Document with Date and Calendar
public class BlogPost {

    private String id;

    private Date created;

    private Calendar updated;

    private String title;

    public BlogPost(String id, Date created, Calendar updated, String title) {
        this.id = id;
        this.created = created;
        this.updated = updated;
        this.title = title;


A populated object can look like:

Example 14. A Document with Date and Calendar - JSON
  "title": "a blog post title",
  "_class": "foo.BlogPost",
  "updated": 1394610843,
  "created": 1394610843897

Optionally, Date can be converted to and from ISO-8601 compliant strings by setting system property org.springframework.data.couchbase.useISOStringConverterForDate to true. If you want to override a converter or implement your own one, this is also possible. The library implements the general Spring Converter pattern. You can plug in custom converters on bean creation time in your configuration. Here’s how you can configure it (in your overridden AbstractCouchbaseConfiguration):

Example 15. Custom Converters
public CustomConversions customConversions() {
    return new CustomConversions(Arrays.asList(FooToBarConverter.INSTANCE, BarToFooConverter.INSTANCE));

public static enum FooToBarConverter implements Converter<Foo, Bar> {

    public Bar convert(Foo source) {
        return /* do your conversion here */;


public static enum BarToFooConverter implements Converter<Bar, Foo> {

    public Foo convert(Bar source) {
        return /* do your conversion here */;


There are a few things to keep in mind with custom conversions:

  • To make it unambiguous, always use the @WritingConverter and @ReadingConverter annotations on your converters. Especially if you are dealing with primitive type conversions, this will help to reduce possible wrong conversions.

  • If you implement a writing converter, make sure to decode into primitive types, maps and lists only. If you need more complex object types, use the CouchbaseDocument and CouchbaseList types, which are also understood by the underlying translation engine. Your best bet is to stick with as simple as possible conversions.

  • Always put more special converters before generic converters to avoid the case where the wrong converter gets executed.

  • For dates, reading converters should be able to read from any Number (not just Long). This is required for N1QL support.

3.4. Optimistic Locking

In certain situations you may want to ensure that you are not overwriting another users changes when you perform a mutation operation on a document. For this you have three choices: Transactions (since Couchbase 6.5), pessimistic concurrency (locking) or optimistic concurrency.

Optimistic concurrency tends to provide better performance than pessimistic concurrency or transactions, because no actual locks are held on the data and no extra information is stored about the operation (no transaction log).

To implement optimistic locking, Couchbase uses a CAS (compare and swap) approach. When a document is mutated, the CAS value also changes. The CAS is opaque to the client, the only thing you need to know is that it changes when the content or a meta information changes too.

In other datastores, similar behavior can be achieved through an arbitrary version field with a incrementing counter. Since Couchbase supports this in a much better fashion, it is easy to implement. If you want automatic optimistic locking support, all you need to do is add a @Version annotation on a long field like this:

Example 16. A Document with optimistic locking.
public class User {

        private long version;

        // constructor, getters, setters...

If you load a document through the template or repository, the version field will be automatically populated with the current CAS value. It is important to note that you shouldn’t access the field or even change it on your own. Once you save the document back, it will either succeed or fail with a OptimisticLockingFailureException. If you get such an exception, the further approach depends on what you want to achieve application wise. You should either retry the complete load-update-write cycle or propagate the error to the upper layers for proper handling.

3.5. Validation

The library supports JSR 303 validation, which is based on annotations directly in your entities. Of course you can add all kinds of validation in your service layer, but this way its nicely coupled to your actual entities.

To make it work, you need to include two additional dependencies. JSR 303 and a library that implements it, like the one supported by hibernate:

Example 17. Validation dependencies

Now you need to add two beans to your configuration:

Example 18. Validation beans
public LocalValidatorFactoryBean validator() {
    return new LocalValidatorFactoryBean();

public ValidatingCouchbaseEventListener validationEventListener() {
    return new ValidatingCouchbaseEventListener(validator());

Now you can annotate your fields with JSR303 annotations. If a validation on save() fails, a ConstraintViolationException is thrown.

Example 19. Sample Validation Annotation
@Size(min = 10)
private String name;

3.6. Auditing

Entities can be automatically audited (tracing which user created the object, updated the object, and at what times) through Spring Data auditing mechanisms.

First, note that only entities that have a @Version annotated field can be audited for creation (otherwise the framework will interpret a creation as an update).

Auditing works by annotating fields with @CreatedBy, @CreatedDate, @LastModifiedBy and @LastModifiedDate. The framework will automatically inject the correct values on those fields when persisting the entity. The xxxDate annotations must be put on a Date field (or compatible, eg. jodatime classes) while the xxxBy annotations can be put on fields of any class T (albeit both fields must be of the same type).

To configure auditing, first you need to have an auditor aware bean in the context. Said bean must be of type AuditorAware<T> (allowing to produce a value that can be stored in the xxxBy fields of type T we saw earlier). Secondly, you must activate auditing in your @Configuration class by using the @EnableCouchbaseAuditing annotation.

Here is an example:

Example 20. Sample Auditing Entity
public class AuditedItem {

  private final String id;

  private String value;

  private String creator;

  private String lastModifiedBy;

  private Date lastModification;

  private Date creationDate;

  private long version;

  //..omitted constructor/getters/setters/...

Notice both @CreatedBy and @LastModifiedBy are both put on a String field, so our AuditorAware must work with String.

Example 21. Sample AuditorAware implementation
public class NaiveAuditorAware implements AuditorAware<String> {

  private String auditor = "auditor";

  public String getCurrentAuditor() {
    return auditor;

  public void setAuditor(String auditor) {
    this.auditor = auditor;

To tie all that together, we use the java configuration both to declare an AuditorAware bean and to activate auditing:

Example 22. Sample Auditing Configuration
@EnableCouchbaseAuditing //this activates auditing
public class AuditConfiguration extends AbstractCouchbaseConfiguration {

    //... a few abstract methods omitted here

    // this creates the auditor aware bean that will feed the annotations
    public NaiveAuditorAware testAuditorAware() {
      return new NaiveAuditorAware();

4. Auto generating keys

This chapter describes how couchbase document keys can be auto-generated using builtin mechanisms. There are two types of auto-generation strategies supported.

The maximum key length supported by couchbase is 250 bytes.

4.1. Configuration

Keys to be auto-generated should be annotated with @GeneratedValue. The default strategy is USE_ATTRIBUTES. Prefix and suffix for the key can be provided as part of the entity itself, these values are not persisted, they are only used for key generation. The prefixes and suffixes are ordered using the order value. The default order is 0, multiple prefixes without order will overwrite the previous. If a value for id is already available, auto-generation will be skipped. The delimiter for concatenation can be provided using delimiter, the default delimiter is ..

Example 23. Annotation for GeneratedValue
public class User {
     @Id @GeneratedValue(strategy = USE_ATTRIBUTES, delimiter = ".")
     private String id;
     private String userPrefix;
     private String userSuffix;

4.2. Key generation using attributes

It is a common practice to generate keys using a combination of the document attributes. Key generation using attributes concatenates all the attribute values annotated with IdAttribute, based on the ordering provided similar to prefixes and suffixes.

Example 24. Annotation for IdAttribute
public class User {
     @Id @GeneratedValue(strategy = USE_ATTRIBUTES)
     private String id;
     private String userid;

4.3. Key generation using uuid

This auto-generation uses UUID random generator to generate document keys consuming 16 bytes of key space. This mechanism is only recommended for test scaffolding.

Example 25. Annotation for Unique key generation
public class User {
     @Id @GeneratedValue(strategy = UNIQUE)
     private String id;

5. 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 Jakarta Persistence API (JPA) module. If you want to use XML configuration 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.

5.1. Core concepts

The central interface in the Spring Data repository abstraction is Repository. It takes the domain class to manage as well as the identifier 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 and ListCrudRepository interfaces provide sophisticated CRUD functionality for the entity class that is being managed.

Example 26. 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.

The methods declared in this interface are commonly referred to as CRUD methods. ListCrudRepository offers equivalent methods, but they return List where the CrudRepository methods return an Iterable.

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.

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

Example 27. PagingAndSortingRepository interface
public interface PagingAndSortingRepository<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 28. 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 29. Derived Delete Query
interface UserRepository extends CrudRepository<User, Long> {

  long deleteByLastname(String lastname);

  List<User> removeByLastname(String lastname);

5.2. 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.

    import org.springframework.data.….repository.config.EnableJpaRepositories;
    class Config { … }
    <?xml version="1.0" encoding="UTF-8"?>
    <beans xmlns="http://www.springframework.org/schema/beans"
       <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.

    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 @EnableJpaRepositories-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:

5.3. 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, you may extend CrudRepository, or one of its variants instead of Repository.

5.3.1. Fine-tuning Repository Definition

There are a few variants how you can get started with your repository interface.

The typical approach is to extend CrudRepository, which gives you methods for CRUD functionality. CRUD stands for Create, Read, Update, Delete. With version 3.0 we also introduced ListCrudRepository which is very similar to the CrudRepository but for those methods that return multiple entities it returns a List instead of an Iterable which you might find easier to use.

If you are using a reactive store you might choose ReactiveCrudRepository, or RxJava3CrudRepository depending on which reactive framework you are using.

If you are using Kotlin you might pick CoroutineCrudRepository which utilizes Kotlin’s coroutines.

Additional you can extend PagingAndSortingRepository, ReactiveSortingRepository, RxJava3SortingRepository, or CoroutineSortingRepository if you need methods that allow to specify a Sort abstraction or in the first case a Pageable abstraction. Note that the various sorting repositories no longer extended their respective CRUD repository as they did in Spring Data Versions pre 3.0. Therefore, you need to extend both interfaces if you want functionality of both.

If you do not want to extend Spring Data interfaces, you can also annotate your repository interface with @RepositoryDefinition. Extending one of the CRUD repository interfaces 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 the CRUD repository into your domain repository. When doing so, you may change the return type of methods. Spring Data will honor the return type if possible. For example, for methods returning multiple entities you may choose Iterable<T>, List<T>, Collection<T> or a VAVR list.

If many repositories in your application should have the same set of methods you can define your own base interface to inherit from. Such an interface must be annotated with @NoRepositoryBean. This prevents Spring Data to try to create an instance of it directly and failing because it can’t determine the entity for that repository, since it still contains a generic type variable.

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

Example 30. 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.

5.3.2. 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 31. 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 32. 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 33. 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 34. 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 35. Annotation-driven configuration of base packages
@EnableJpaRepositories(basePackages = "com.acme.repositories.jpa")
@EnableMongoRepositories(basePackages = "com.acme.repositories.mongo")
class Configuration { … }

5.4. 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.

5.4.1. 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 EnableJpaRepositories 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.

5.4.2. 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 36. 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 “Paging, Iterating Large Results, Sorting”.

5.4.3. 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).

5.4.4. Paging, Iterating Large Results, Sorting

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 37. 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.
Which Method is Appropriate?

The value provided by the Spring Data abstractions is perhaps best shown by the possible query method return types outlined in the following table below. The table shows which types you can return from a query method

Table 4. Consuming Large Query Results
Method Amount of Data Fetched Query Structure Constraints


All results.

Single query.

Query results can exhaust all memory. Fetching all data can be time-intensive.


All results.

Single query.

Query results can exhaust all memory. Fetching all data can be time-intensive.


Chunked (one-by-one or in batches) depending on Stream consumption.

Single query using typically cursors.

Streams must be closed after usage to avoid resource leaks.


Chunked (one-by-one or in batches) depending on Flux consumption.

Single query using typically cursors.

Store module must provide reactive infrastructure.


Pageable.getPageSize() + 1 at Pageable.getOffset()

One to many queries fetching data starting at Pageable.getOffset() applying limiting.

A Slice can only navigate to the next Slice.

  • Slice provides details whether there is more data to fetch.

  • Offset-based queries becomes inefficient when the offset is too large because the database still has to materialize the full result.

  • Window provides details whether there is more data to fetch.

  • Offset-based queries becomes inefficient when the offset is too large because the database still has to materialize the full result.


Pageable.getPageSize() at Pageable.getOffset()

One to many queries starting at Pageable.getOffset() applying limiting. Additionally, COUNT(…) query to determine the total number of elements can be required.

Often times, COUNT(…) queries are required that are costly.

  • Offset-based queries becomes inefficient when the offset is too large because the database still has to materialize the full result.

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 38. 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 39. 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 40. Defining sort expressions by using the Querydsl API
QSort sort = QSort.by(QPerson.firstname.asc())

5.4.5. 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 41. 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.

5.4.6. 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 42. 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() { … }

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

  private final 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.

5.4.7. 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 43. 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 44. 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.

5.4.8. 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’s nullability annotations. They provide a tooling-friendly approach and opt-in null checks during runtime, as follows:

  • @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.

  • @NonNull: Used on a parameter or return value that must not be null (not needed on a parameter and return value where @NonNullApi applies).

  • @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 45. 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 46. 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 47. 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.

5.4.9. Asynchronous Query Results

You can run repository queries asynchronously by using 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)
1 Use java.util.concurrent.Future as the return type.
2 Use a Java 8 java.util.concurrent.CompletableFuture as the return type.

5.5. Creating Repository Instances

This section covers how to create instances and bean definitions for the defined repository interfaces.

5.5.1. Java Configuration

Use the store-specific @EnableJpaRepositories annotation on a Java configuration class to define a configuration for repository activation. For an introduction to Java-based configuration of the Spring container, see JavaConfig in the Spring reference documentation.

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

Example 48. 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.

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

  <jpa: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. Bean names for nested repository interfaces are prefixed with their enclosing type name. The base package attribute allows wildcards so that you can define a pattern of scanned packages.

5.5.3. 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 filter elements inside the repository declaration. The semantics are exactly equivalent to the elements in Spring’s component filters. For details, see the Spring reference documentation for these elements.

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

Example 50. Using filters
@EnableJpaRepositories(basePackages = "com.acme.repositories",
    includeFilters = { @Filter(type = FilterType.REGEX, pattern = ".*SomeRepository") },
    excludeFilters = { @Filter(type = FilterType.REGEX, pattern = ".*SomeOtherRepository") })
class ApplicationConfiguration {

  EntityManagerFactory entityManagerFactory() {
    // …
<repositories base-package="com.acme.repositories">
  <context:include-filter type="regex" expression=".*SomeRepository" />
  <context:exclude-filter type="regex" expression=".*SomeOtherRepository" />

The preceding example includes all interfaces ending with SomeRepository and excludes those ending with SomeOtherRepository from being instantiated.

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

5.6. Custom Implementations for Spring Data Repositories

Spring Data provides various options to create query methods with little coding. But when those options don’t fit your needs you can also provide your own custom implementation for repository methods. This section describes how to do that.

5.6.1. 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 52. Interface for custom repository functionality
interface CustomizedUserRepository {
  void someCustomMethod(User user);
Example 53. 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 54. 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 55. 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 56. 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 57. 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 58. Customized repository interfaces
interface UserRepository extends CrudRepository<User, Long>, CustomizedSave<User> {

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

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 a postfix defaulting 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 59. Configuration example
@EnableJpaRepositories(repositoryImplementationPostfix = "MyPostfix")
class Configuration { … }
<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 60. 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 61. Manual wiring of custom implementations
class MyClass {
  MyClass(@Qualifier("userRepositoryImpl") UserRepository userRepository) {
<repositories base-package="com.acme.repository" />

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

5.6.2. 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 62. 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 configuration, you can do so by using the repositoryBaseClass, as shown in the following example:

Example 63. Configuring a custom repository base class
@EnableJpaRepositories(repositoryBaseClass = MyRepositoryImpl.class)
class ApplicationConfiguration { … }
<repositories base-package="com.acme.repository"
     base-class="….MyRepositoryImpl" />

5.7. 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 64. 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 the following a Spring Data repository methods are called:

  • save(…), saveAll(…)

  • delete(…), deleteAll(…), deleteAllInBatch(…), deleteInBatch(…)

Note, that these methods take the aggregate root instances as arguments. This is why deleteById(…) is notably absent, as the implementations might choose to issue a query deleting the instance and thus we would never have access to the aggregate instance in the first place.

5.8. 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.

5.8.1. 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 65. 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 66. 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")


5.8.2. 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 67. Enabling Spring Data web support
class WebConfiguration {}
<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" />

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.

Basic Web Support
Enabling Spring Data web support in XML

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 68. 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 69. 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 5. 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 Page and Slice

Spring HATEOAS ships with a representation model class (PagedModel/SlicedModel) that allows enriching the content of a Page or Slice instance with the necessary Page/Slice metadata as well as links to let the clients easily navigate the pages. The conversion of a Page to a PagedModel is done by an implementation of the Spring HATEOAS RepresentationModelAssembler interface, called the PagedResourcesAssembler. Similarly Slice instances can be converted to a SlicedModel using a SlicedResourcesAssembler. The following example shows how to use a PagedResourcesAssembler as a controller method argument, as the SlicedResourcesAssembler works exactly the same:

Example 70. Using a PagedResourcesAssembler as controller method argument
class PersonController {

  private final PersonRepository repository;

  // Constructor omitted

  HttpEntity<PagedModel<Person>> people(Pageable pageable,
    PagedResourcesAssembler assembler) {

    Page<Person> people = repository.findAll(pageable);
    return ResponseEntity.ok(assembler.toModel(people));

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

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

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

  • The PagedModel 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/people) 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 JSON envelope format shown here doesn’t follow any formally specified structure and it’s not guaranteed stable and we might change it at any time. It’s highly recommended to enable the rendering as a hypermedia-enabled, official media type, supported by Spring HATEOAS, like HAL. Those can be activated by using its @EnableHypermediaSupport annotation. Find more information in the Spring HATEOAS reference documentation.

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.toModel(…) 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 71. 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.
You can register a QuerydslBinderCustomizerDefaults bean holding default Querydsl bindings before applying specific bindings from the repository or @QuerydslPredicate.

5.8.3. 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 72. 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 73. 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 reference documentation for details. The following example shows how to unmarshall a repository populator with JAXB:

Example 74. 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" />


6. Couchbase repositories

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

By default, operations are backed by Key/Value if they are single-document operations and the ID is known. For all other operations by default N1QL queries are generated, and as a result proper indexes must be created for performant data access.

Note that you can tune the consistency you want for your queries (see Querying with consistency) and have different repositories backed by different buckets (see [couchbase.repository.multibucket])

6.1. Configuration

While support for repositories is always present, you need to enable them in general or for a specific namespace. If you extend AbstractCouchbaseConfiguration, just use the @EnableCouchbaseRepositories annotation. It provides lots of possible options to narrow or customize the search path, one of the most common ones is basePackages.

Also note that if you are running inside spring boot, the autoconfig support already sets up the annotation for you so you only need to use it if you want to override the defaults.

Example 75. Annotation-Based Repository Setup
@EnableCouchbaseRepositories(basePackages = {"com.couchbase.example.repos"})
public class Config extends AbstractCouchbaseConfiguration {

An advanced usage is described in [couchbase.repository.multibucket].

6.2. Usage

In the simplest case, your repository will extend the CrudRepository<T, String>, where T is the entity that you want to expose. Let’s look at a repository for a UserInfo:

Example 76. A UserInfo repository
import org.springframework.data.repository.CrudRepository;

public interface UserRepository extends CrudRepository<UserInfo, String> {

Please note that this is just an interface and not an actual class. In the background, when your context gets initialized, actual implementations for your repository descriptions get created and you can access them through regular beans. This means you will save lots of boilerplate code while still exposing full CRUD semantics to your service layer and application.

Now, let’s imagine we @Autowire the UserRepository to a class that makes use of it. What methods do we have available?

Table 6. Exposed methods on the UserRepository
Method Description

UserInfo save(UserInfo entity)

Save the given entity.

Iterable<UserInfo> save(Iterable<UserInfo> entity)

Save the list of entities.

UserInfo findOne(String id)

Find a entity by its unique id.

boolean exists(String id)

Check if a given entity exists by its unique id.

Iterable<UserInfo> findAll()

Find all entities by this type in the bucket.

Iterable<UserInfo> findAll(Iterable<String> ids)

Find all entities by this type and the given list of ids.

long count()

Count the number of entities in the bucket.

void delete(String id)

Delete the entity by its id.

void delete(UserInfo entity)

Delete the entity.

void delete(Iterable<UserInfo> entities)

Delete all given entities.

void deleteAll()

Delete all entities by type in the bucket.

Now that’s awesome! Just by defining an interface we get full CRUD functionality on top of our managed entity.

While the exposed methods provide you with a great variety of access patterns, very often you need to define custom ones. You can do this by adding method declarations to your interface, which will be automatically resolved to requests in the background, as we’ll see in the next sections.

6.3. Repositories and Querying

6.3.1. N1QL based querying

Prerequisite is to have created a PRIMARY INDEX on the bucket where the entities will be stored.

Here is an example:

Example 77. An extended UserInfo repository with N1QL queries
public interface UserRepository extends CrudRepository<UserInfo, String> {

    @Query("#{#n1ql.selectEntity} WHERE role = 'admin' AND #{#n1ql.filter}")
    List<UserInfo> findAllAdmins();

    List<UserInfo> findByFirstname(String fname);

Here we see two N1QL-backed ways of querying.

The first method uses the Query annotation to provide a N1QL statement inline. SpEL (Spring Expression Language) is supported by surrounding SpEL expression blocks between #{ and }. A few N1QL-specific values are provided through SpEL:

  • #n1ql.selectEntity allows to easily make sure the statement will select all the fields necessary to build the full entity (including document ID and CAS value).

  • #n1ql.filter in the WHERE clause adds a criteria matching the entity type with the field that Spring Data uses to store type information.

  • #n1ql.bucket will be replaced by the name of the bucket the entity is stored in, escaped in backticks.

  • #n1ql.scope will be replaced by the name of the scope the entity is stored in, escaped in backticks.

  • #n1ql.collection will be replaced by the name of the collection the entity is stored in, escaped in backticks.

  • #n1ql.fields will be replaced by the list of fields (eg. for a SELECT clause) necessary to reconstruct the entity.

  • #n1ql.delete will be replaced by the delete from statement.

  • #n1ql.returning will be replaced by returning clause needed for reconstructing entity.

We recommend that you always use the selectEntity SpEL and a WHERE clause with a filter SpEL (since otherwise your query could be impacted by entities from other repositories).

String-based queries support parametrized queries. You can either use positional placeholders like “$1”, in which case each of the method parameters will map, in order, to $1, $2, $3…​ Alternatively, you can use named placeholders using the “$someString” syntax. Method parameters will be matched with their corresponding placeholder using the parameter’s name, which can be overridden by annotating each parameter (except a Pageable or Sort) with @Param (eg. @Param("someString")). You cannot mix the two approaches in your query and will get an IllegalArgumentException if you do.

Note that you can mix N1QL placeholders and SpEL. N1QL placeholders will still consider all method parameters, so be sure to use the correct index like in the example below:

Example 78. An inline query that mixes SpEL and N1QL placeholders
@Query("#{#n1ql.selectEntity} WHERE #{#n1ql.filter} AND #{[0]} = $2")
public List<User> findUsersByDynamicCriteria(String criteriaField, Object criteriaValue)

This allows you to generate queries that would work similarly to eg. AND name = "someName" or AND age = 3, with a single method declaration.

You can also do single projections in your N1QL queries (provided it selects only one field and returns only one result, usually an aggregation like COUNT, AVG, MAX…​). Such projection would have a simple return type like long, boolean or String. This is NOT intended for projections to DTOs.

Another example:
#{#n1ql.selectEntity} WHERE #{#n1ql.filter} AND test = $1
is equivalent to
SELECT #{#n1ql.fields} FROM #{#n1ql.collection} WHERE #{#n1ql.filter} AND test = $1

A practical application of SpEL with Spring Security

SpEL can be useful when you want to do a query depending on data injected by other Spring components, like Spring Security. Here is what you need to do to extend the SpEL context to get access to such external data.

First, you need to implement an EvaluationContextExtension (use the support class as below):

class SecurityEvaluationContextExtension extends EvaluationContextExtensionSupport {

  public String getExtensionId() {
    return "security";

  public SecurityExpressionRoot getRootObject() {
    Authentication authentication = SecurityContextHolder.getContext().getAuthentication();
    return new SecurityExpressionRoot(authentication) {};

Then all you need to do for Spring Data Couchbase to be able to access associated SpEL values is to declare a corresponding bean in your configuration:

EvaluationContextExtension securityExtension() {
    return new SecurityEvaluationContextExtension();

This could be useful to craft a query according to the role of the connected user for instance:

@Query("#{#n1ql.selectEntity} WHERE #{#n1ql.filter} AND " +
"role = '?#{hasRole('ROLE_ADMIN') ? 'public_admin' : 'admin'}'")
List<UserInfo> findAllAdmins(); //only ROLE_ADMIN users will see hidden admins

Delete query example:

@Query("#{#n1ql.delete} WHERE #{#n1ql.filter} AND " +
"username = $1 #{#n1ql.returning}")
UserInfo removeUser(String username);

The second method uses Spring-Data’s query derivation mechanism to build a N1QL query from the method name and parameters. This will produce a query looking like this: SELECT …​ FROM …​ WHERE firstName = "valueOfFnameAtRuntime". You can combine these criteria, even do a count with a name like countByFirstname or a limit with a name like findFirst3ByLastname…​

Actually the generated N1QL query will also contain an additional N1QL criteria in order to only select documents that match the repository’s entity class.

Most Spring-Data keywords are supported: .Supported keywords inside @Query (N1QL) method names

Keyword Sample N1QL WHERE clause snippet



lastName = a AND firstName = b



lastName = a OR firstName = b



field = a



field != a



field BETWEEN a AND b



field < a



field ⇐ a



field > a



field >= a



field IS NULL






field LIKE "a" - a should be a String containing % and _ (matching n and 1 characters)



field NOT LIKE "a" - a should be a String containing % and _ (matching n and 1 characters)



field LIKE "a%" - a should be a String prefix



field LIKE "%a" - a should be a String suffix



field LIKE "%a%" - a should be a String



field NOT LIKE "%a%" - a should be a String



field IN array - note that the next parameter value (or its children if a collection/array) should be compatible for storage in a JsonArray)



field NOT IN array - note that the next parameter value (or its children if a collection/array) should be compatible for storage in a JsonArray)



field = TRUE



field = FALSE



REGEXP_LIKE(field, "a") - note that the ignoreCase is ignored here, a is a regular expression in String form



field IS NOT MISSING - used to verify that the JSON contains this attribute



field = a ORDER BY lastname DESC



LOWER(field) = LOWER("a") - a must be a String

You can use both counting queries and Limiting Query Results features with this approach.

With N1QL, another possible interface for the repository is the PagingAndSortingRepository one (which extends CrudRepository). It adds two methods:

Table 7. Exposed methods on the PagingAndSortingRepository
Method Description

Iterable<T> findAll(Sort sort);

Allows to retrieve all relevant entities while sorting on one of their attributes.

Page<T> findAll(Pageable pageable);

Allows to retrieve your entities in pages. The returned Page allows to easily get the next page’s Pageable as well as the list of items. For the first call, use new PageRequest(0, pageSize) as Pageable.

You can also use Page and Slice as method return types as well with a N1QL backed repository.
If pageable and sort parameters are used with inline queries, there should not be any order by, limit or offset clause in the inline query itself otherwise the server would reject the query as malformed.

6.3.2. Automatic Index Management

By default, it is expected that the user creates and manages optimal indexes for their queries. Especially in the early stages of development, it can come in handy to automatically create indexes to get going quickly.

For N1QL, the following annotations are provided which need to be attached to the entity (either on the class or the field):

  • @QueryIndexed: Placed on a field to signal that this field should be part of the index

  • @CompositeQueryIndex: Placed on the class to signal that an index on more than one field (composite) should be created.

  • @CompositeQueryIndexes: If more than one CompositeQueryIndex should be created, this annotation will take a list of them.

For example, this is how you define a composite index on an entity:

Example 79. Composite index on two fields with ordering
@CompositeQueryIndex(fields = {"id", "name desc"})
public class Airline {
   String id;

	String name;

	public Airline(String id, String name) {
		this.id = id;

	public String getId() {
		return id;

	public String getName() {
		return name;


By default, index creation is disabled. If you want to enable it you need to override it on the configuration:

Example 80. Enable auto index creation
protected boolean autoIndexCreation() {
 return true;

6.3.3. Querying with consistency

By default repository queries that use N1QL use the NOT_BOUNDED scan consistency. This means that results return quickly, but the data from the index may not yet contain data from previously written operations (called eventual consistency). If you need "ready your own write" semantics for a query, you need to use the @ScanConsistency annotation. Here is an example:

Example 81. Using a different scan consistency
public interface AirportRepository extends PagingAndSortingRepository<Airport, String> {

	@ScanConsistency(query = QueryScanConsistency.REQUEST_PLUS)
	Iterable<Airport> findAll();


6.3.4. DTO Projections

Spring Data Repositories usually return the domain model when using query methods. However, sometimes, you may need to alter the 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 Person {

  @Id @GeneratedValue
  private Long id;
  private String firstName, lastName;

  private Address address;

public class Address {

  @Id @GeneratedValue
  private Long id;
  private String street, state, country;


This Person has several attributes:

  • id is the primary key

  • firstName and lastName are data attributes

  • address is a link to another domain object

Now assume we create a corresponding repository as follows:

interface PersonRepository extends CrudRepository<Person, Long> {

  Person findPersonByFirstName(String firstName);

Spring Data will return the domain object including all of its attributes. There are two options just to retrieve the address attribute. One option is to define a repository for Address objects like this:

interface AddressRepository extends CrudRepository<Address, Long> {}

In this situation, using PersonRepository will still return the whole Person object. Using AddressRepository will return just the Address.

However, what if you do not want to expose address details at all? You can offer the consumer of your repository service an alternative by defining one or more projections.

Example 82. Simple Projection
interface NoAddresses {  (1)

  String getFirstName(); (2)

  String getLastName();  (3)

This projection has the following details:

1 A plain Java interface making it declarative.
2 Export the firstName.
3 Export the lastName.

The NoAddresses projection only has getters for firstName and lastName meaning that it will not serve up any address information. The query method definition returns in this case NoAdresses instead of Person.

interface PersonRepository extends CrudRepository<Person, Long> {

  NoAddresses findByFirstName(String firstName);

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 firstName, then the getter method must be named getFirstName otherwise Spring Data is not able to look up the source property.

7. Reactive Couchbase repository

7.1. Introduction

This chapter describes the reactive repository support for couchbase. This builds on the core repository support explained in Couchbase repositories. So make sure you’ve got a sound understanding of the basic concepts explained there.

7.2. Reactive Composition Libraries

The Couchbase Java SDK 3.x moved from RxJava to Reactor, so it blends in very nicely with the reactive spring ecosystem.

Reactive Couchbase repositories provide project Reactor wrapper types and can be used by simply extending from one of the library-specific repository interfaces:

  • ReactiveCrudRepository

  • ReactiveSortingRepository

7.3. Usage

Let’s create a simple entity to start with:

Example 83. Sample Person entity
public class Person {

  private String id;
  private String firstname;
  private String lastname;
  private Address address;

  // … getters and setters omitted

A corresponding repository implementation may look like this:

Example 84. Basic repository interface to persist Person entities
public interface ReactivePersonRepository extends ReactiveSortingRepository<Person, Long> {

  Flux<Person> findByFirstname(String firstname);

  Flux<Person> findByFirstname(Publisher<String> firstname);

  Flux<Person> findByFirstnameOrderByLastname(String firstname, Pageable pageable);

  Mono<Person> findByFirstnameAndLastname(String firstname, String lastname);

For JavaConfig use the @EnableReactiveCouchbaseRepositories annotation. The annotation carries the very same attributes like the namespace element. If no base package is configured the infrastructure will scan the package of the annotated configuration class.

Also note that if you are using it in a spring boot setup you likely can omit the annotation since it is autoconfigured for you.

Example 85. JavaConfig for repositories
class ApplicationConfig extends AbstractCouchbaseConfiguration {
	// ... (see configuration for details)

As our domain repository extends ReactiveSortingRepository it provides you with CRUD operations as well as methods for sorted access to the entities. Working with the repository instance is just a matter of dependency injecting it into a client.

Example 86. Sorted access to Person entities
public class PersonRepositoryTests {

    ReactivePersonRepository repository;

    public void sortsElementsCorrectly() {
      Flux<Person> persons = repository.findAll(Sort.by(new Order(ASC, "lastname")));

7.4. Repositories and Querying

Spring Data’s Reactive Couchbase comes with full querying support already provided by the blocking Repositories and Querying

8. Template & direct operations

The template provides lower level access to the underlying database and also serves as the foundation for repositories. Any time a repository is too high-level for you needs chances are good that the templates will serve you well. Note that you can always drop into the SDK directly through the beans exposed on the AbstractCouchbaseConfiguration.

8.1. Supported operations

The template can be accessed through the couchbaseTemplate and reactiveCouchbaseTemplate beans out of your context. Once you’ve got a reference to it, you can run all kinds of operations against it. Other than through a repository, in a template you need to always specify the target entity type which you want to get converted.

The templates use a fluent-style API which allows you to chain in optional operators as needed. As an example, here is how you store a user and then find it again by its ID:

Example 87. Fluent template access
// Create an Entity
User user = new User(UUID.randomUUID().toString(), "firstname", "lastname");

// Upsert it

// Retrieve it again
User found = couchbaseTemplate.findById(User.class).one(user.getId());

If you wanted to use a custom (by default durability options from the @Document annotation will be used) durability requirement for the upsert operation you can chain it in:

Example 88. Upsert with durability
User modified = couchbaseTemplate

In a similar fashion, you can perform a N1QL operation:

Example 89. N1QL query on the template
final List<User> foundUsers = couchbaseTemplate

8.2. Sub-Document Operations

Couchbase supports Sub-Document Operations. This section documents how to use it with Spring Data Couchbase.

Sub-Document operations may be quicker and more network-efficient than full-document operations such as upsert or replace because they only transmit the accessed sections of the document over the network.

Sub-Document operations are also atomic, in that if one Sub-Document mutation fails then all will, allowing safe modifications to documents with built-in concurrency control.

Currently Spring Data Couchbase supports only sub document mutations (remove, upsert, replace and insert).

Mutation operations modify one or more paths in the document. The simplest of these operations is upsert, which, similar to the fulldoc-level upsert, will either modify the value of an existing path or create it if it does not exist:

Following example will upsert the city field on the address of the user, without trasfering any additional user document data.

Example 90. MutateIn upsert on the template
User user = new User();
// id field on the base document id required

8.2.1. Executing Multiple Sub-Document Operations

Multiple Sub-Document operations can be executed at once on the same document, allowing you to modify several Sub-Documents at once. When multiple operations are submitted within the context of a single mutateIn command, the server will execute all the operations with the same version of the document.

To execute several mutation operations the method chaining can be used.

Example 91. MutateIn Multiple Operations
    .withInsertPaths("roles", "subuser.firstname")

8.2.2. Concurrent Modifications

Concurrent Sub-Document operations on different parts of a document will not conflict so by default the CAS value will be not be supplied when executing the mutations. If CAS is required then it can be provided like this:

Example 92. MutateIn With CAS
User user = new User();
// id field on the base document id required
// @Version field should have a value for CAS to be supplied

9. Couchbase Transactions

Couchbase supports Distributed Transactions. This section documents how to use it with Spring Data Couchbase.

9.1. Requirements

  • Couchbase Server 6.6.1 or above.

  • Spring Data Couchbase 5.0.0-M5 or above.

  • NTP should be configured so nodes of the Couchbase cluster are in sync with time. The time being out of sync will not cause incorrect behavior, but can impact metadata cleanup.

  • The entity class must have an @Version Long property to hold the CAS value of the document.

9.2. Overview

The Spring Data Couchbase template operations insert, find, replace and delete and repository methods that use those calls can participate in a Couchbase Transaction. They can be executed in a transaction by using the @Transactional annotation, the CouchbaseTransactionalOperator, or in the lambda of a Couchbase Transaction.

9.3. Getting Started & Configuration

Couchbase Transactions are normally leveraged with a method annotated with @Transactional. The @Transactional operator is implemented with the CouchbaseTransactionManager which is supplied as a bean in the AbstractCouchbaseConfiguration. Couchbase Transactions can be used without defining a service class by using CouchbaseTransactionOperator which is also supplied as a bean in AbtractCouchbaseConfiguration. Couchbase Transactions can also be used directly using Spring Data Couchbase operations within a lambda Using Transactions

9.4. Transactions with @Transactional

@Transactional defines as transactional a method or all methods on a class.

When this annotation is declared at the class level, it applies as a default to all methods of the declaring class and its subclasses.

9.4.1. Attribute Semantics

In this release, the Couchbase Transactions ignores the rollback attributes. The transaction isolation level is read-committed;

Example 93. Transaction Configuration and Use by @Transactional
The Configuration
@EnableTransactionManagement (1)
static class Config extends AbstractCouchbaseConfiguration {

  // Usual Setup
  @Override public String getConnectionString() { /* ... */ }
  @Override public String getUserName() { /* ... */ }
  @Override public String getPassword() { /* ... */ }
  @Override public String getBucketName() { /* ... */ }

  // Customization of transaction behavior is via the configureEnvironment() method
  @Override protected void configureEnvironment(final Builder builder) {
The Transactional Service Class

Note that the body of @Transactional methods can be re-executed if the transaction fails. It is imperative that everthing in the method body be idempotent.

import reactor.core.publisher.Mono;
import reactor.core.publisher.Flux;

import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;

final CouchbaseOperations personOperations;
final ReactiveCouchbaseOperations reactivePersonOperations;

@Service (2)
public class PersonService {

  final CouchbaseOperations operations;
  final ReactiveCouchbaseOperations reactiveOperations;

  public PersonService(CouchbaseOperations ops, ReactiveCouchbaseOperations reactiveOps) {
    operations = ops;
    reactiveOperations = reactiveOps;

  // no annotation results in this method being executed not in a transaction
  public Person save(Person p) {
    return operations.save(p);

  public Person changeFirstName(String id, String newFirstName) {
    Person p = operations.findById(Person.class).one(id); (3)
    return operations.replaceById(Person.class).one(p.withFirstName(newFirstName);

  public Mono<Person> reactiveChangeFirstName(String id, String newFirstName) {
    return personOperationsRx.findById(Person.class).one(person.id())
        .flatMap(p -> personOperationsRx.replaceById(Person.class).one(p.withFirstName(newFirstName)));

Using the @Transactional Service.
@Autowired PersonService personService; (4)

Person walterWhite = new Person( "Walter", "White");
Person p = personService.save(walterWhite); // this is not a transactional method
Person renamedPerson = personService.changeFirstName(walterWhite.getId(), "Ricky"); (5)

Functioning of the @Transactional method annotation requires

  1. the configuration class to be annotated with @EnableTransactionManagement;

  2. the service object with the annotated methods must be annotated with @Service;

  3. the body of the method is executed in a transaction.

  4. the service object with the annotated methods must be obtained via @Autowired.

  5. the call to the method must be made from a different class than service because calling an annotated method from the same class will not invoke the Method Interceptor that does the transaction processing.

9.5. Transactions with CouchbaseTransactionalOperator

CouchbaseTransactionalOperator can be used to construct a transaction in-line without creating a service class that uses @Transactional. CouchbaseTransactionalOperator is available as a bean and can be instantiated with @Autowired. If creating one explicitly, it must be created with CouchbaseTransactionalOperator.create(manager) (NOT TransactionalOperator.create(manager)).

Example 94. Transaction Access Using TransactionalOperator.execute()
@Autowired TransactionalOperator txOperator;
@Autowired ReactiveCouchbaseTemplate reactiveCouchbaseTemplate;

Flux<Person> result = txOperator.execute((ctx) ->
    .flatMap(p -> reactiveCouchbaseTemplate.replaceById(Person.class).one(p.withFirstName("Walt")))

9.6. Transactions Directly with the SDK

Spring Data Couchbase works seamlessly with the Couchbase Java SDK for transaction processing. Spring Data Couchbase operations that can be executed in a transaction will work directly within the lambda of a transactions().run() without involving any of the Spring Transactions mechanisms. This is the most straight-forward way to leverage Couchbase Transactions in Spring Data Couchbase.

Please see the Reference Documentation

Example 95. Transaction Access - Blocking
@Autowired CouchbaseTemplate couchbaseTemplate;

TransactionResult result = couchbaseTemplate.getCouchbaseClientFactory().getCluster().transactions().run(ctx -> {
  Person p = couchbaseTemplate.findById(Person.class).one(personId);
Example 96. Transaction Access - Reactive
@Autowired ReactiveCouchbaseTemplate reactiveCouchbaseTemplate;

Mono<TransactionResult> result = reactiveCouchbaseTemplate.getCouchbaseClientFactory().getCluster().reactive().transactions()
  .run(ctx ->
      .flatMap(p -> reactiveCouchbaseTemplate.replaceById(Person.class).one(p.withFirstName("Walt")))

10. Collection Support

Couchbase supports Scopes and Collections. This section documents on how to use it with Spring Data Couchbase.

The try-cb-spring sample application is a working example of using Scopes and Collections in Spring Data Couchbase.

The 2021 Couchbase Connect presentation on Collections in Spring Data can be found at Presentation Only and Presentation with Slide Deck

10.1. Requirements

  • Couchbase Server 7.0 or above.

  • Spring Data Couchbase 4.3.1 or above.

10.2. Getting Started & Configuration

10.2.1. Scope and Collection Specification

There are several mechanisms of specifying scopes and collections, and these may be combined, or one mechanism may override another. First some definitions for scopes and collections. An unspecified scope indicates that the default scope is to be used, likewise, an unspecified collection indicates that the default collection is to be used. There are only three combinations of scopes and collections that are valid. (1) the default scope and the default collection; (2) the default scope and a non-default collection; and (3) a non-default scope and a non-default collection. It is not possible to have a non-default scope and a default collection as non-default scopes do not contain a default collections, neither can one be created.

A scope can be specified in the configuration:

static class Config extends AbstractCouchbaseConfiguration {

    // Usual Setup
    @Override public String getConnectionString() { /* ... */ }

    // optionally specify the scope in the Configuration
    protected String getScopeName() {
        return "myScope"; // or a variable etc.;


Scopes and Collections can be specified as annotations on entity classes and repositories:

public class Airport {...
public interface AirportRepository extends CouchbaseRepository<Airport, String> ...

Scopes and Collections can be specified on templates using the inScope(scopeName) and inCollection(collectionName) fluent APIs:

List<Airport> airports = template.findByQuery(Airport.class).inScope("archived").all()

Scopes and Collections can be specified on repositories that extend DynamicProxyable using the withScope(scopeName) and withCollection(collectionName) APIs:

public interface AirportRepository extends CouchbaseRepository<Airport, String>, DynamicProxyable<AirportRepository>{...}
List<Airport> airports = airportRepository.withScope("archived").findByName(iata);
The order of precedence is:
  1. inScope()/inCollection() of the template fluent api

  2. withScope()/withCollection() of the template/repository object

  3. annotation of the repository method

  4. annotation of the repository interface

  5. annotation of the entity object

  6. getScope() of the configuration

11. Couchbase Field Level Encrytpion

Couchbase supports Field Level Encryption. This section documents how to use it with Spring Data Couchbase.

11.1. Requirements

  • Spring Data Couchbase 5.0.0-RC1 or above.

11.2. Overview

Fields annotated with com.couchbase.client.java.encryption.annotation.Encrypted (@Encrypted) will be automatically encrypted on write and decrypted on read. Unencrypted fields can be migrated to encrypted by specifying @Encrypted(migration = Encrypted.Migration.FROM_UNENCRYPTED).

11.3. Getting Started & Configuration

11.3.1. Dependencies

Field Level Encryption is available with the dependency ( see Field Level Encryption )


HashiCorp Vault Transit integration requires Spring Vault


11.3.2. Providing a CryptoManager

A CryptoManager needs to be provided by overriding the cryptoManager() method in AbstractCouchbaseConfiguration. This CryptoManager will be used by Spring Data Couchbase and also by Couchbase Java SDK direct calls made from a CouchbaseClientFactory.

protected CryptoManager cryptoManager() {
  KeyStore javaKeyStore = KeyStore.getInstance("MyKeyStoreType");
  FileInputStream fis = new java.io.FileInputStream("keyStoreName");
  char[] password = { 'a', 'b', 'c' };
  javaKeyStore.load(fis, password);
  Keyring keyring = new KeyStoreKeyring(javaKeyStore, keyName -> "swordfish");

  // AES-256 authenticated with HMAC SHA-512. Requires a 64-byte key.
  AeadAes256CbcHmacSha512Provider provider = AeadAes256CbcHmacSha512Provider.builder().keyring(keyring).build();

  CryptoManager cryptoManager = DefaultCryptoManager.builder().decrypter(provider.decrypter())
  return cryptoManager;

11.3.3. Defining a Field as Encrypted.

  1. @Encrypted defines a field as encrypted.

  2. @Encrypted(migration = Encrypted.Migration.FROM_UNENCRYPTED) defines a field that may or may not be encrypted when read. It will be encrypted when written.

  3. @Encrypted(encrypter = "<encrypterAlias>") specifies the alias of the encrypter to use for encryption. Note this is not the algorithm, but the name specified when adding the encrypter to the CryptoManager.

11.3.4. Example

Example 97. AbstractCouchbaseConfiguration
static class Config extends AbstractCouchbaseConfiguration {

  // Usual Setup
  @Override public String getConnectionString() { /* ... */ }
  @Override public String getUserName() { /* ... */ }
  @Override public String getPassword() { /* ... */ }
  @Override public String getBucketName() { /* ... */ }

  /* provide a cryptoManager */
  protected CryptoManager cryptoManager() {
    KeyStore javaKeyStore = KeyStore.getInstance("MyKeyStoreType");
    FileInputStream fis = new java.io.FileInputStream("keyStoreName");
    char[] password = { 'a', 'b', 'c' };
    javaKeyStore.load(fis, password);
    Keyring keyring = new KeyStoreKeyring(javaKeyStore, keyName -> "swordfish");

    // AES-256 authenticated with HMAC SHA-512. Requires a 64-byte key.
    AeadAes256CbcHmacSha512Provider provider = AeadAes256CbcHmacSha512Provider.builder().keyring(keyring).build();

    CryptoManager cryptoManager = DefaultCryptoManager.builder().decrypter(provider.decrypter())
    return cryptoManager;

Example 98. The Annotation in the Document
public class AddressWithEncStreet extends Address {

    private @Encrypted String encStreet;
Example 99. Usage in Code
AddressWithEncStreet address = new AddressWithEncStreet(); // plaintext address with encrypted street
address.setCity("Santa Clara");
address.setEncStreet("Olcott Street");
Example 100. Resulting Document
  "_class": "AddressWithEncStreet",
   "city": "Santa Clara",
   "encrypted$encStreet": {
     "alg": "AEAD_AES_256_CBC_HMAC_SHA512",
     "ciphertext": "A/tJALmtixTxqj77ZUcUgMklIt3372DKD7l5FvbCzHNJMplbgQEv0RgSbxIfiRNr+uW2H7cokkcCW/F5YnQoXA==",
     "kid": "myKey"

12. ANSI Joins

This chapter describes hows ANSI joins can be used across entities. Since 5.5 version, Couchbase server provides support for ANSI joins for joining documents using fields. Previous versions allowed index & lookup joins, which were supported in SDC only by querying directly through the SDK.

Relationships between entities across repositories can be one to one or one to many. By defining such relationships, a synchronized view of associated entities can be fetched.

12.1. Configuration

Associated entities can be fetched by annotating the entity’s property reference with @N1qlJoin. The prefix lks refers to left-hand side key space (current entity) and rks refers to the right-hand side key space (associated entity). The required element for @N1qlJoin annotation is the on clause, a boolean expression representing the join condition between the left-hand side (lks) and the right-hand side (rks), which can be fields, constant expressions or any complex N1QL expression. There could also be an optional where clause specified on the annotation for the join, similarly using lks to refer the current entity and rks to refer the associated entity.

Example 101. Annotation for ANSI Join
public class Author {
      String id;

      String name;

      @N1qlJoin(on = "lks.name=rks.authorName")
      List<Book> books;

      @N1qlJoin(on = "lks.name=rks.name")
      Address address;

12.2. Lazy fetching

Associated entities can be lazily fetched upon the first access of the property, this could save on fetching more data than required when loading the entity. To load the associated entities lazily, @N1qlJoin annotation’s element fetchType has to be set to FetchType.LAZY. The default is FetchType.IMMEDIATE.

Example 102. Configuration for lazy fetch
@N1qlJoin(on = "lks.name=rks.authorName", fetchType = FetchType.LAZY)
List<Book> books;

12.3. ANSI Join Hints

12.3.1. Use Index Hint

index element on the @N1qlJoin can be used to provided the hint for the lks (current entity) index and rightIndex element can be used to provided the rks (associated entity) index.

12.3.2. Hash Join Hint

If the join type is going to be hash join, the hash side can be specified for the rks (associated entity). If the associated entity is on the build side, it can be specified as HashSide.BUILD else HashSide.PROBE.

12.3.3. Use Keys Hint

keys element on the @N1qlJoin annotation can be used to specify unique document keys to restrict the join key space.

13. Caching

This chapter describes additional support for caching and @Cacheable.

13.1. Configuration & Usage

Technically, caching is not part of spring-data, but is implemented directly in the spring core. Most database implementations in the spring-data package can’t support @Cacheable, because it is not possible to store arbitrary data.

Couchbase supports both binary and JSON data, so you can get both out of the same database.

To make it work, you need to add the @EnableCaching annotation and configure the cacheManager bean:

Example 103. AbstractCouchbaseConfiguration for Caching
public class Config extends AbstractCouchbaseConfiguration {
    // general methods

  public CouchbaseCacheManager cacheManager(CouchbaseTemplate couchbaseTemplate) throws Exception {
  CouchbaseCacheManager.CouchbaseCacheManagerBuilder builder = CouchbaseCacheManager.CouchbaseCacheManagerBuilder
    builder.withCacheConfiguration("mySpringCache", CouchbaseCacheConfiguration.defaultCacheConfig());
    return builder.build();

The persistent identifier can then be used on the @Cacheable annotation to identify the cache manager to use (you can have more than one configured).

Once it is set up, you can annotate every method with the @Cacheable annotation to transparently cache it in your couchbase bucket. You can also customize how the key is generated.

Example 104. Caching example
@Cacheable(value="persistent", key="'longrunsim-'+#time")
public String simulateLongRun(long time) {
    try {
    } catch(Exception ex) {
        System.out.println("This shouldnt happen...");
    return "I've slept " + time + " miliseconds.;

If you run the method multiple times, you’ll see a set operation happening first, followed by multiple get operations and no sleep time (which fakes the expensive execution). You can store whatever you want, if it is JSON of course you can access it through views and look at it in the Web UI.

Note that to use cache.clear() or cache.invalidate(), the bucket must have a primary key. :leveloffset: -1

14. 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 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 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.