Tuning Semantic Search for Real Performance Gains
Practical strategies for balancing speed and recall in vector search systems, from choosing the right index to managing embedding dimensions and metadata filters.
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Practical strategies for balancing speed and recall in vector search systems, from choosing the right index to managing embedding dimensions and metadata filters.
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Supabase's new S3-compatible Vector Buckets offer a different approach to vector storage compared to traditional in-Postgres methods like HNSW or IVFFlat. See a direct comparison of speed, cost, and scale.
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