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Benchmarks produce clean numbers - but do they reflect what actually happens when users apply filters, facets, and hybrid queries in realistic document collections in production?
In this session, we evaluate the real-world performance of three vector search options available to OpenSearch users: Lucene’s built-in HNSW, the Faiss engine integration, and jVector, an open-source vector search plugin. While all engines publish compelling benchmark results and advertise strong scalability, most existing comparisons focus on isolated ANN performance rather than realistic query patterns.
Using identical datasets, queries, and filter selectivity, we examine how latency, recall, and throughput change once Boolean filters, aggregations, and hybrid retrieval are introduced. We break down where performance differences originate inside OpenSearch - including index construction behavior, memory usage, concurrency, and merge strategies.
Attendees will leave with practical guidance on when each engine is the right default choice, how to interpret vendor and community benchmarks critically, and how to design vector search evaluations that reflect real production systems.
Fernando is the CTO of Zeta Alpha, an Amsterdam-based startup helping High-Tech and R&D Enterprises take their Generative AI projects to production. With a PhD in theoretical physics and a hacker (builder) past, Fernando brings a unique blend of theoretical knowledge and hands-on... Read More →
Thursday April 16, 2026 10:20 - 11:00 CEST Bohemia 2
