Redis Caching & Data Store
Microsecond-level performance for real-time applications
In-Memory Speed
Redis is an in-memory data store delivering microsecond-level latency. Database queries take milliseconds, disk I/O takes milliseconds: Redis takes microseconds. Storing frequently accessed data in Redis eliminates database hits, reducing load and improving response times. Users experience faster applications.
Redis is more than caching. It's a data structure server: strings, lists, sets, sorted sets, hashes, streams, bitmaps. Pub/Sub for real-time messaging. Transactions for ACID operations on multiple keys. Persistence options: RDB snapshots or AOF logs. Replication for high availability. Cluster mode for scaling to terabytes across multiple nodes.
We use Redis for session management, rate limiting, leaderboards, real-time feeds, message queues, distributed locks. Cache invalidation strategies. Cluster topology. Monitoring. The result: applications that feel responsive and serve peak loads without melting databases.
Redis Use Cases
Caching
Cache database query results, API responses, computed data. TTL expires old data automatically. Application checks Redis first, hits database only on cache miss.
Sessions
Store user sessions with fast lookups. Distributed sessions across multiple application servers. Automatic expiration of inactive sessions.
Real-Time Features
Leaderboards, live notifications, activity feeds, user presence. Pub/Sub for broadcasting updates to connected clients.
Rate Limiting
Track request counts per user/IP. Enforce rate limits: allow X requests per minute. Atomic operations handle concurrent requests.
Queues
Job queues, message queues, task distribution. Producers push jobs, workers pop and process. Reliable delivery with persistence.
Distributed Locks
Coordinate across distributed systems. Prevent race conditions. Atomic operations ensure correctness. Expiration prevents deadlocks.
Need Redis?
Let's architect high-performance caching and real-time systems with Redis.
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