Which following statements are true about Spring Data? (Choose two.)

Question

Options

• ASpring Data implementations exist for many data storage types, such as MongoDB, Neo4j, and
• BSpring Data works by applying the JPA annotations to data stores such as MongoDB, Neo4j,
• CSpring Data can greatly reduce the amount of "boilerplate" code typically needed for data
• DSpring Data is specifically designed for JPA, JDBC, and relational database access only.
• ESpring Data cannot be used together with Spring MVC.

• A
  89% (56)
• B
  6% (4)
• D
  2% (1)
• E
  3% (2)

Explanation

A is correct because Spring Data is a family of projects that provides consistent, familiar abstractions over many different data stores - including MongoDB (document), Neo4j (graph), Redis (key-value), Cassandra, and relational databases via JPA/JDBC. It is explicitly not limited to one technology.

C is correct because Spring Data's core value proposition is eliminating boilerplate: by defining a repository interface (e.g., extends JpaRepository<User, Long>), Spring automatically generates the implementation - no manual EntityManager calls, no hand-written SQL for standard CRUD operations.

B is wrong because Spring Data does not apply JPA annotations to non-relational stores. Each Spring Data module uses its own mapping annotations (e.g., @Document for MongoDB, @Node for Neo4j) - JPA annotations are specific to JPA-compatible stores.

D is wrong because it contradicts A - Spring Data explicitly supports non-relational databases. JPA/JDBC support is just one sub-project (spring-data-jpa, spring-data-jdbc).

E is wrong because Spring Data and Spring MVC are fully compatible and commonly used together in the same application (e.g., a REST controller calling a Spring Data repository).

Memory tip: Think of Spring Data as a universal remote - one consistent API (Repository) that works across many "TVs" (data stores). The two truths are: many stores supported (A) and less code written (C).

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