ShareChat’s Ivan Burmistrov and Andrei Manakov walk through how they built a low latency ML Feature Store based on ScyllaDB which initially failed to meet the scalability requirements and failed on 1 million features per second load, but has been successfully scaled 1000 times to handle 1 billing features per second without scaling the underlying database.
