Google Contributes Data Partitioning Capability to Hibernate
Hibernate Shards, contributed by Google, offers critical data clustering and support for horizontal partitioning (also called sharding) to Hibernate. Now, customers can keep their data in more than one relational database for whatever reason-too much data or to isolate certain datasets, for instance-without added complexity when building and managing applications. Hibernate Shards is designed to encapsulate and reduce the complexity of building applications that work with sharded datasets.Today also marks updated releases of Hibernate Annotations and Hibernate Entity Manager 3.3.0GA. Among the included features:
"The ability to improve scalability by seamlessly distributing data across multiple databases is crucial for enterprise applications that transact against large or physically distributed datasets," said Google software engineer Max Ross. "We're pleased to contribute our implementation for horizontal partitioning to open source via Hibernate, and we look forward to working with the Hibernate team to further this technology."
- Improved support for legacy mapping, including better native SQL customization support and fetching strategies.
- Out-of-the-box integration between all Hibernate components. Users have asked for flexibility of components so they can implement Hibernate in whichever manner suits their development. Now there's less configuration hassle so users can start developing right away.
- Improved integration in third party environments such as IBM WebSphere, BEA WebLogic, and pure Java Persistence solutions.