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Spring Data Release Train - Spring 4.0, Limiting Queries, SpEL, ALPS

| by Bienvenido David Follow 1 Followers on Sep 26, 2014. Estimated reading time: 1 minute |

Spring Data release train Evans is now generally available. The release train includes 11 Spring Data modules that help developers build data access layers on top of both relational and non-relational data stores. The major themes of this release are:

  • Migration from Spring 3.2 to Spring 4.0.
  • Support for the keywords top and first in deriving limiting queries.
  • Support for MongoDB 2.6 features in the aggregation framework.
  • SpEL-based parameter expressions support in Spring Data JPA queries.
  • Support for Sentinels in Spring Data Redis.
  • ALPS and excerpt projections in Spring Data REST.
  • Support for custom implementations in the CDI extensions.
  • Multi-store configuration and setup.
  • Use of Asciidoctor for reference documentation.
  • Support for geo-location queries in Spring Data Elasticsearch.

The 11 modules included in this release train are:

  • Spring Data Commons 1.9. Contains technology neutral repository interfaces and a persistence metadata model.
  • Spring Data JPA 1.7. Provides enhanced Spring support for JPA based data access layers.
  • Spring Data MongoDB 1.6. Provides a POJO centric model for interacting with a MongoDB DBCollection.
  • Spring Data Neo4j 3.2. Provides a POJO based programming model that simplifies the creation of neo4j applications.
  • Spring Data Solr 1.3. Provides integration with the Apache Solr search engine.
  • Spring Data Couchbase 1.2. Provides a Spring-based programming model for Couchbase Server as a document database and cache while retaining store-specific features and capabilities.
  • Spring Data Cassandra 1.1. Provides a low-level CqlTemplate for working with Cassandra, and a high level module for repositories and lightweight POJO persistence.
  • Spring Data Elasticsearch 1.1. Provides integration with the Elasticsearch search engine.
  • Spring Data GemFire 1.5. Create Spring-powered applications using Pivotal GemFire as a distributed, data management platform.
  • Spring Data Redis 1.4. Provides integration with Redis cache and store.
  • Spring Data REST 2.2. Takes your JPA repositories and front-ends them with HTTP, allowing you full CRUD capability over your entities.

The various example projects have been updated and are a good starting point to get started with the new Spring Data features. The next Spring Data Release Train is Fowler with M1 estimated at calendar week 43.

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