About Redis Basics

Data types, caching pattern, operational commands, pitfalls. Part of the DevTools Surf developer suite. Browse more tools in the Info / Guides collection.

Use Cases

• Backend developers implementing API response caching layers
• DevOps engineers setting up session storage for horizontally scaled apps
• Real-time app developers using Redis Pub/Sub for message broadcasting
• Data engineers using sorted sets for leaderboards and rate limiting

Tips

• Start with the caching pattern section for the most common use case
• Check the data types overview to pick the right structure for your data
• Review the operational commands for monitoring memory and connections

Fun Facts

• Redis was created by Salvatore Sanfilippo (antirez) in 2009. The name stands for 'Remote Dictionary Server.'
• Redis can handle over 100,000 SET operations per second on a single instance because all operations run in a single-threaded event loop with in-memory data.
• Redis Labs rebranded to Redis Inc. in 2023 and changed the license from BSD to dual-license (RSALv2/SSPL) in March 2024, sparking community forks like Valkey.

FAQ

What is Redis?

In-memory data store. Fast (sub-millisecond), supports strings, hashes, lists, sets, sorted sets, streams. Used for cache, session store, pub/sub, queues.

Common data-type choices?

String for KV cache. Hash for object fields (user:123 {name, email}). Sorted set for leaderboards and time-series. Stream for event logs.

Caching pattern?

Cache-aside: check cache, hit returns; miss → fetch from DB → store in cache. Set TTL on writes to avoid stale data. Use SETNX for distributed locks.

What breaks in production?

Memory exhaustion (no eviction policy set), connection pool saturation, blocking operations (KEYS on production). Always set maxmemory + policy, use SCAN not KEYS.