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Vector Database

A database optimized for similarity search over embeddings.

Plain-English explanation

Vector databases help retrieve semantically similar chunks, products, documents, or user memories. Examples include Pinecone, Weaviate, Milvus, Qdrant, and pgvector.

Why it matters

Vector Database matters because it affects how AI systems are designed, evaluated, priced, or trusted. Knowing the term helps you ask better questions and avoid vague implementation decisions.

  • Ask how it changes quality, cost, speed, or safety.
  • Look for concrete examples in the workflow you are building.
  • Document the tradeoff before choosing a tool or architecture.