Data & AI

Redis

An in-memory data store used for caching, session management, pub/sub messaging, and rate limiting in production systems.

01What it is

In production terms.

Redis stores key-value data in memory with optional persistence to disk. It supports strings, hashes, lists, sets, sorted sets, and streams, with sub-millisecond read latency. Redis Cluster and Sentinel provide high availability and horizontal scaling.

Codeaxes adds Redis to nearly every production stack to cache expensive database queries, store session tokens, implement rate limiters, and decouple services via pub/sub. It prevents PostgreSQL from becoming a bottleneck under read-heavy traffic patterns.

02Fit

Best-fit use cases.

  1. 01API response caching with TTL-based invalidation on data changes
  2. 02Session storage for authenticated web and mobile applications
  3. 03Rate limiting per API key or user to protect backend services
  4. 04Pub/sub channels for real-time notification delivery

03Trade-offs

Benefits and limits.

Benefits

  • Sub-millisecond latency for hot-path reads and writes
  • Versatile data structures cover caching, queuing, and leaderboards
  • Atomic operations enable safe concurrent counter and lock patterns
  • Managed options on AWS ElastiCache, Memorystore, and Azure Cache

Limitations

  • Memory-bound, dataset size is limited by available RAM unless tiered storage is configured
  • Not a replacement for persistent relational or document databases
  • Persistence modes trade durability for performance and require configuration tuning

04Ecosystem

Compatible technologies.

05In the field

Example applications.

  • SaaS API caching user permission lookups to reduce PostgreSQL query load
  • Real-time leaderboard for a gamified mobile app using sorted sets
  • Distributed rate limiter protecting OpenAI proxy endpoints from abuse

Use Redis on a Codeaxes engagement.