In this session, you'll learn how to use Spring Data to rapidly develop repositories for a variety of database types, including relational (JPA and JDBC), document (Mongo), graph (Neo4j), and others (Redis, Cassandra, CouchBase, etc).
For decades, relational databases and SQL have enjoyed their position as the leading choice for data persistence. Even though many alternative database types have emerged in recent years, the relational database is still a top choice for a general purposes data store and will not likely be usurped from its position any time soon. When it comes to working with relational data, Java developers have several options.
But relational databases are not a one-size-fits-all solution. Thankfully, there are many options for data persistence, including relational, document, graph, key-value, and column-store databases, each presenting their unique way of handling data suitable for different problems.
Spring Data makes it easy to work with various databases by offering a programming model that is consistent, regardless of which type of database you're working with. And regardless of the database you're dealing with, you will find that Spring Data eliminates a lot of boilerplate code.
Craig Walls is a principal engineer with Pivotal and is the author of Spring in Action and Spring Boot in Action. He's a zealous promoter of the Spring Framework, speaking frequently at local user groups and conferences and writing about Spring. When he's not slinging code, Craig is planning his next trip to Disney World or Disneyland and spending as much time as he can with his wife, two daughters, 2 birds and 3 dogs.