Data Caching

High-performance caching with in-memory LRU, Redis, and tiered strategies.

In-Memory Cache

Fast LRU cache with TTL support for single-instance deployments.

Tiered Cache (L1 + L2)

Combine fast local cache with distributed Redis for best of both worlds.

Latency Comparison

<1ms
L1 Memory Hit
1-5ms
L2 Redis Hit
10-100ms
Database Query

Cache Invalidation

Multiple strategies for keeping cache data fresh.

Cache Keys

Structured keys with tenant and parameter support.

Metrics & Monitoring

Cache Backends

Backend Use Case Latency Shared
MemoryCache Single instance, hot data ~100ns ❌
RedisCache Distributed, shared state ~1-5ms ✅
TieredCache Best of both ~100ns (L1 hit) ✅

Best Practices

✅ Do

  • Include tenant ID in cache keys for multi-tenant apps
  • Set appropriate TTLs based on data volatility
  • Monitor hit rates and adjust capacity
  • Use tag-based invalidation for related data

❌ Don't

  • Cache sensitive data without encryption
  • Skip cache invalidation on writes
  • Use very long TTLs without invalidation strategy