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AI & models

Vector database

Vector store

A database built specifically to store embeddings — those meaning-as-numbers lists — and to find the closest matches to a query almost instantly, even across millions of entries. A regular database is great at exact lookups ('find order #4821'); a vector database is great at 'find the things most similar in meaning to this.'
Why it matters

It's the memory behind RAG and search-by-meaning — the part that quickly fetches the handful of relevant passages an AI should read before it answers.

Part of Search over your own documents (RAG)

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