A vector database stores data as high-dimensional numerical embeddings and retrieves items by semantic similarity rather than exact keywords. It's the memory layer behind semantic search and RAG.
Vector databases (e.g. Pinecone, Weaviate, pgvector) index embeddings so you can ask "what is similar in meaning to this?" — the foundation of semantic search, recommendations and retrieval-augmented AI.
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