Here's How ShareChat Scaled Their ML Feature Store 1000X Without Scaling the Database

ShareChat successfully scaled its ML feature store from 1M to 1B features/sec using ScyllaDB, advanced caching, and schema optimizations. This performance engineering approach avoided database scaling and significantly improved latency and cache hit rates.

Listen