About this episode

Patrick and Jason explain vector databases, covering embeddings, similarity metrics, and how these systems manage high-dimensional vectors.

Patrick and Jason explain vector databases by starting with embeddings, similarity metrics, and approximate nearest-neighbor search. They discuss how these systems store and query high-dimensional vectors and where tools like pgvector, Weaviate, Pinecone, and Milvus fit.

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