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Dev.to
6/25/2026
Vibe-Memory Part 3: pgvector Performance Optimization - How I Cut Query Time From 800ms to 15ms

Vibe-Memory Part 3: pgvector Performance Optimization - How I Cut Query Time From 800ms to 15ms

Short summary

Developer optimized pgvector performance in a personal AI memory assistant using three techniques: switching from IVFFlat to HNSW indexing (5x faster), reducing embedding dimensions from 1536 to 512 (2x faster), and running VACUUM ANALYZE. Combined improvements cut query times from 800ms to 50ms.

  • •IVFFlat to HNSW index switch reduced query time from 800ms to 150ms
  • •Reducing embeddings from 1536 to 512 dimensions cut time to 70ms with minimal quality loss
  • •VACUUM ANALYZE maintenance made performance consistent, gaining another 20ms improvement

Generated with AI, which can make mistakes.

#ai-tools#ai-agents
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