Redis

A section on Redis from scratch — a fast in-memory store that the backend most often needs as a cache, but which can do much more. What it is and when to use it, what data structures it offers, how to cache correctly, use it for locks and counters, connect it to Spring Boot, and operate it in production. Best read in order.

• What Redis is: in-memory storage for backend developers — Redis is a fast in-memory key-value store. We look at why it works instantly, when to use it, and how to connect from Java.
• Redis data structures: String, Hash, List, Set, Sorted Set, and more — Which data structures Redis has, how they differ, and when to use each one — from counters to leaderboards and queues.
• Caching patterns in Redis — Cache-aside, write-through, write-behind, expiration, and invalidation: how to build a cache on Redis correctly so you don't serve stale data or hit a cache stampede.
• Redis beyond caching: locks, rate limiting, queues, and Pub/Sub — How to use Redis for distributed locks, rate limiting, queues, and event-based messaging — with command and Java/Spring examples.
• Redis in Spring Boot: RedisTemplate, @Cacheable, and Spring Session — How to connect Redis to Spring Boot via Spring Data Redis: RedisTemplate, serialization, caching via @Cacheable, and sessions via Spring Session.
• Operating Redis: persistence, memory, replication — How Redis stores data on disk, manages memory, and stays available during failures — RDB, AOF, Sentinel, Cluster, and monitoring.