Fast like a cache, priced like storage: Benchmarking Aerospike on Feast

Aerospike announced a Feast integration that allows it to serve as an online store for real-time feature retrieval and evaluated its performance with Feast’s public benchmark harness against published Redis and DynamoDB results across varying entity counts, feature counts, and request rates. The tests used an end-to-end setup involving a load generator, Python feature server, and online store, though the results were gathered on different hardware and at different times, so the comparison emphasizes workload patterns rather than exact latency ratios. Under smaller and moderate requests, Aerospike reportedly delivered latency comparable to Redis and lower than DynamoDB, while at higher loads it maintained successful requests through the tested 100 RPS level for workloads of 100 entities and 50 features, where Redis and DynamoDB showed declining success rates. For a larger 100-entity, 250-feature workload, Aerospike was the only tested store to complete requests, though only at lower request rates, indicating limits in the full serving stack rather than necessarily the databases alone. The report attributes Aerospike’s performance and potential cost advantage to its Hybrid Memory Architecture, which retains indexes in memory while placing feature data on SSD, and illustrates that this approach could require substantially less RAM than an all-memory Redis deployment as feature-store datasets grow, although actual costs and performance depend on deployment-specific workload, infrastructure, and latency requirements.

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