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Building High-Performance Vector Databases for Retrieval-Augmented Generation (RAG)

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Building High-Performance Vector Databases for Retrieval-Augmented Generation (RAG)

The Vector Search Breakthrough

Semantic search maps meaning, not exact terms.

Minimal pgvector query

SQL
SELECT id, title
FROM knowledge_chunks
ORDER BY embedding <=> :query_embedding
LIMIT 5;

Core architecture

  • Embed docs on ingestion
  • Store vectors with metadata
  • Retrieve top-k context
  • Re-rank before final answer

[!TIP] Keep chunks short and semantically coherent for better retrieval quality.

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