Key-value database
In-memory data structures at microsecond speed.
An in-memory key-value store with rich data structures — strings, hashes, lists, sets, sorted sets, streams — used for caching, sessions, queues, rate limiting and real-time features.
RedisIntermediateOne slow command blocks every client. Find it with SLOWLOG and LATENCY DOCTOR, then replace KEYS with SCAN, split big keys, delete with UNLINK and tame fork pauses.
#caching#performance#troubleshooting
RedisAdvancedWhat changes at scale: stampede locks, probabilistic early refresh, stale-while-revalidate, hot keys, negative caching, pipelining, timeouts, circuit breakers, warmup, clustering and alerts.
#caching#nosql#performance
RedisIntermediateRedis and Memcached compared by mechanism: threading, slab vs allocator memory, expiry and eviction, persistence, clustering, meta commands, operations and licensing, with a recommendation.
#caching#internals#nosql
RedisAdvancedEach Redis cache pattern with code, guarantees and failure modes, then the stale-set race, why delete beats update, versioned writes, outbox and CDC invalidation, and what to use for which data.
#caching#concurrency#nosql
RedisBeginnerWhat to cache, string vs hash, key naming, how TTLs and expiry work, maxmemory and every eviction policy, a working cache-aside example, and the commands to measure and secure a Redis cache.
#caching#configuration#nosql
RedisIntermediateWrites fail and reads still work. Understand Redis eviction policies, find what's filling memory, and pick the right fix depending on whether Redis is a cache or a datastore.
#caching#configuration#nosql
RedisBeginnerPut Redis in front of your database the right way — choose a caching pattern, set sane TTLs, and avoid stampedes and stale data.
#caching#nosql#performance
