Spring Data gets a release train
The Spring Data developers have decided to coordinate the publication of the various Spring Data modules with a regularly scheduled release train. The first release train of modules has just arrived, synchronising the GA (general availability) releases of six Spring Data modules: Spring Data Commons 1.4, Spring Data JPA 1.2, Spring Data MongoDB 1.1, Spring Data Neo4j 2.1, Sprint Data Gemfire 1.2 and Spring Data REST Exporters 1.0.
Spring Data is an umbrella project at the VMware division SpringSource for open source data access technologies for the Spring Framework. With this release train approach, the plan is to coordinate the modules so that they interoperate better. As part of this, the developers have added annotation support to the Spring Data Commons allowing developers to use, for example,
@EnableJPARepositories, in code for XML-free configuration.
The MongoDB module is described as the one "shipping with the most new user-visible features". These include improved GridFS support for easy storage and retrieval of files in MongoDB, a CDI extension which allows MongoDB to be injected into Java EE 6 applications and two community contributions (support for JSR303 validation and optimistic locking). The Neo4J module added support for the creation of unique entities and the Gemfire module has had its namespace revised to more closely match GemFire's cache configuration.
A new addition to the Spring Data projects, the Spring Data REST Exporters, allows developers to expose entities managed by Spring Data through an HTTP interface. The exposed APIs support accessing entities and queries and there is extensive support for controlling who can access the API and underlying entities. Only the JPA-based repositories are currently supported but the developers hope to add support for others in future versions. This release represents a final iteration of the 1.x branch of Spring Data Commons and the next stop is a milestone release for a future 2.0 with some API changes, including the addition of a common auditing mechanism.
Further details of changes and plans for the future of Spring Data are in Oliver Gierke's blog posting. Links for Artifacts, JavaDocs, Documentation and Change Logs are in the Spring Data release train announcement.