Spring Data Framework
The Spring Data Framework provides a unified configuration model and easy to use APIs for developing solutions for big data ingest/export. The purpose is to unify and ease the access to different kinds of persistence stores, both relational database systems and NoSQL data stores. Spring supports integration by providing a simple model for building enterprise integration solutions while maintaining the separation of concerns that is essential for producing maintainable, testable code.
Spring Data makes it easy to build applications across a wide range of new data access technologies (NoSQL and Hadoop) and provides a consistent programming model that retains NoSQL-specific features and capabilities. It helps you develop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow.
Spring Data’s repositories allow you to write an interface with finder methods defined according to a given set of conventions (which may vary depending on the kind of persistence store you are using) - it wil then provide an appropriate implementation of that interface at runtime.
Spring for Apache Hadoop is a framework for application developers to take advantage of the features of both Hadoop and Spring. Spring for Hadoop helps to resolve the issue of having poorly constructed Hadoop applications, which usually consist of command line utilities, scripts and pieces of code stitched together. It provides a consistent programming and configuration model across a wide range of Hadoop ecosystem projects.