What is Redis?

Definition

Redis (Remote Dictionary Server) is an in-memory data structure store that can be used as a database, cache, message broker, and queue. Created by Salvatore Sanfilippo in 2009, it's one of the most popular key-value stores in the world.

Redis stores data primarily in memory, which makes it extraordinarily fast - typically handling hundreds of thousands of operations per second. It supports persistence to disk for durability and offers replication for high availability.

Common Use Cases

• Caching: Cache database queries, API responses, and session data with automatic expiration.
• Session storage: Store user sessions with fast read/write access and TTL support.
• Rate limiting: Implement API rate limiting using Redis counters and expiration.
• Real-time leaderboards: Sorted sets enable real-time ranking systems.
• Pub/Sub messaging: Lightweight publish/subscribe messaging for real-time notifications.
• Job queues: Background job processing with tools like Celery, RQ, or Bull.
• Distributed locks: Implement distributed locking for concurrent systems.

Redis with Python

Redis integrates seamlessly with Python backends:

• redis-py: Official Python client with sync and async support.
• Celery: Uses Redis as a message broker for distributed task queues.
• FastAPI caching: Cache endpoint responses using Redis for dramatic performance improvements.
• Django cache backend: Native Redis cache backend in Django 4.0+.

Code Example

import redis.asyncio as redis
from fastapi import FastAPI
import json

app = FastAPI()
cache = redis.Redis(host='localhost', port=6379, decode_responses=True)

@app.get("/users/{user_id}")
async def get_user(user_id: int):
    # Check cache first
    cached = await cache.get(f"user:{user_id}")
    if cached:
        return json.loads(cached)

    # Fetch from database
    user = await fetch_user_from_db(user_id)

    # Cache for 5 minutes
    await cache.setex(f"user:{user_id}", 300, json.dumps(user))
    return user

Frequently Asked Questions

Is Redis a database or a cache?

Redis can be both. It started as an in-memory cache but has evolved into a full database with persistence (RDB snapshots and AOF logs), replication, clustering, and Lua scripting. Many use it as both: primary data store for real-time data and cache for slower backend databases.

What happens to Redis data if the server crashes?

Redis offers two persistence mechanisms: RDB (point-in-time snapshots) and AOF (append-only file that logs every write). With AOF set to 'always', you lose at most one command. Most production setups use both RDB and AOF together.