Redis is the in-memory data store that started as a key-value cache and grew into a Swiss-army knife: cache layer, session store, pub/sub, message queue (via streams), rate limiter, leaderboard backend, and distributed lock. The single-threaded core handles hundreds of thousands of operations per second; clustering distributes data across nodes when one machine isn't enough.
Day-to-day Redis is straightforward. The interesting parts — and where most courses focus — are the data structure choices (when to use sorted sets vs hashes vs streams), the persistence model (RDB snapshots vs AOF), the operational concerns (replication, sentinel, cluster mode), and the patterns that show up in real systems (cache stampede prevention, distributed locks via Redlock, rate limiting via sliding windows).
