ShareChat Cuts Feature Store Costs

ShareChat optimized its ML feature store after scaling to 1 billion features per second. The company reduced costs by implementing tiered storage and compressing less frequently accessed features. Engineers can apply similar strategies to balance performance and expense in high-throughput ML systems.