PocketClawvol. 1 · 2026

Vector database

Database optimised for similarity search over high-dimensional embeddings.

Vector databases store embeddings — fixed-length numerical representations of text or other content — and retrieve nearest-neighbours efficiently. Used in RAG, semantic search, recommendation. Common 2026 choices for self-hosted setups: Postgres with pgvector (simplest), Qdrant (fast), Chroma (Python-friendly).

Related terms

RAG (Retrieval-Augmented Generation)AI agent

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