Redis Is a Network Hop
Every Redis call is a TCP round-trip. At 96 concurrent workers doing FHE operations, a single Redis container serialized all connections. Our throughput dropped from 1.51M to 136K operations per second — an 11x regression.
The Fix: In-Process DashMap
Cachee replaced Redis in our hot path with an in-process Rust cache:
- 0.085 microseconds per lookup (vs ~50 microseconds for Redis RTT)
- 44x faster than even raw STARK proof verification
- Zero TCP contention — no serialization bottleneck
- CacheeLFU eviction with Count-Min Sketch admission (512 KiB constant memory)
When Redis Still Makes Sense
Redis is fine for sorted sets, pub/sub, and multi-instance shared state. But if you are doing millions of lookups per second on a single instance, an in-process cache eliminates the network entirely.
We kept Redis for leaderboard sorted sets only. Everything else — rate limiting, sessions, ZKP proof caching — moved to Cachee.
Result: 1,667,875 authenticated operations per second on a single Graviton4 instance.
Cachee — post-quantum cache engine.
Introducing H33-74. 74 bytes. Any computation. Post-quantum attested. Forever.
