Spring Batch plugs into Neo4j and MongoDB
Spring Data support and Java configuration are highlights of the new Spring Batch release from Pivotal's SpringSource division. Spring Batch is a lightweight framework for developing batch applications and builds upon the Spring framework's development approach. It is designed to address the need for periodically executed business critical tasks. The new 2.2.0 version of Spring Batch follows in the footsteps of other Spring projects which are integrating NoSQL databases and other "big data" sources using the Spring Data project and moving over to a programmatic configuration model rather than an XML-based one.
In Spring Batch 2.2.0, there is Spring Data read/write support for Neo4J and MongoDB and write-only support for Gemfire. There are also wrappers that can handle CRUD and Paged/Sorted repositories of data. The Spring projects are moving to support configuration through Java code and Spring Batch is following this trend with an
@EnableBatchProcessing annotation and auto-wiring of job repositories, launcher, registries and transaction managers.
Other changes include the ability to read and write to AMQP messaging endpoints by using the Spring AMQP project, support for passing parameters to a job which aren't part of identifying the new job, SQLFire support for storing job repository data, and updated dependencies such as now supporting Spring 3.2 and Hibernate 4. Other changes in Spring Batch are covered in the change log. Spring Batch is available to download or can be installed as Maven artifacts. The Apache 2.0 licensed source code is published on the project's GitHub repository.