Redis for Developers: Data Structures and Use Cases

Redis is an in-memory data store known for sub-millisecond responses. It's more than a key-value cache: each data structure solves a specific class of problems elegantly.

Strings: cache values and counters

SET page:/pricing "<html>..." EX 300     # cache for 5 minutes
GET page:/pricing
INCR stats:signups:2026-10-11            # atomic counter

Hashes: objects

HSET user:42 name "Asha" plan "pro" credits 120
HGET user:42 plan
HINCRBY user:42 credits -5

Lists: simple queues and recent items

LPUSH recent:user:42 "post:991"
LTRIM recent:user:42 0 9                 # keep the last 10
LRANGE recent:user:42 0 -1

Sets: unique membership

SADD online:users 42 77 105
SISMEMBER online:users 42
SINTER followers:42 followers:77         # mutual followers

Sorted sets: rankings and time-ordered data

ZADD leaderboard 1520 "asha" 1810 "ravi"
ZREVRANGE leaderboard 0 9 WITHSCORES     # top 10
ZADD delayed:jobs 1760190000 "job:1"     # score = run-at timestamp

Streams: event logs with consumer groups

XADD orders * id 42 total 1499
XREADGROUP GROUP billing worker-1 COUNT 10 STREAMS orders >

Using Redis from Node.js

import { createClient } from 'redis';

const redis = createClient({ url: process.env.REDIS_URL });
await redis.connect();

await redis.set('greeting', 'hello', { EX: 60 });
const value = await redis.get('greeting');

Remember

• Data lives in RAM, so size your instance for your dataset.
• Use clear key names with prefixes (user:42, cache:product:7) and set TTLs on cache keys.
• Configure persistence deliberately if Redis holds data you can't rebuild.