Aerospike now available as a Feast online store

Feast now supports Aerospike as an online feature store, enabling machine learning teams to serve growing feature workloads with low, predictable latency without requiring all data to reside in memory. Aerospike’s Hybrid Memory Architecture keeps indexes in RAM while storing feature data on SSD, aiming to deliver near in-memory performance at lower cost and greater scale for latency-sensitive applications such as fraud detection, personalization, and real-time bidding. Benchmarks using Feast’s end-to-end testing harness found that Aerospike matched an in-memory store for small requests and remained responsive under heavier workloads where the in-memory option degraded, while retaining feature data on SSD. The integration is configured through Feast’s standard online-store interface, supports selectively routing highly latency-sensitive feature views to memory-backed namespaces, and recommends grouping commonly requested features together or precomputing wide feature services to reduce reads. Users are advised to pin Feast versions and validate failover, TTL, and namespace placement in staging before production deployment.

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