What is…

Vector database

A database built to store embeddings and quickly find the most similar ones.

When you have thousands of documents chopped into chunks and embedded, you need to find the handful most relevant to a question in milliseconds. Vector databases (Pinecone, Weaviate, pgvector in Postgres, and others) do exactly that: "give me the 5 nearest neighbors to this question's embedding."

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Related terms

Embeddings

Lists of numbers that represent meaning — texts about similar things end up close together.

RAG (Retrieval-Augmented Generation)

Looking up relevant documents first, then having the model answer using them — grounded, current, citable.

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← Embeddings RAG →