Caching sits between your application and the database. A cache hit returns data in microseconds; a database query takes milliseconds. For frequently-read, infrequently-changed data, caching is the highest-leverage performance improvement. Spring Cache Abstraction Spring’s cache abstraction lets you add caching with annotations — the backing store (Caffeine, Redis, Hazelcast) is swappable: @Service @RequiredArgsConstructor public class ProductService { private final ProductRepository repository; @Cacheable("products") // cache the result public Product findById(UUID id) { return repository.

Caching reduces database load and response latency. Spring Boot’s cache abstraction lets you add caching with annotations, then swap the implementation (Caffeine, Redis, multi-level) without changing your business code. This guide covers Caffeine for in-JVM caching, Redis for distributed caching, and a multi-level cache that combines both. Spring Cache Abstraction Spring’s cache abstraction uses three annotations: Annotation Behaviour @Cacheable Cache the return value. On subsequent calls, return from cache without executing the method.