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Vector Database

Database optimized for storing and searching high-dimensional vector embeddings.

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Definition

Vector databases are specialized systems for efficient similarity search over embedding vectors.

Core Operations: - Store vectors with metadata - Find k-nearest neighbors - Filter by metadata - Update/delete vectors

Search Algorithms: - HNSW (Hierarchical Navigable Small World) - IVF (Inverted File Index) - PQ (Product Quantization) - Exact nearest neighbor (small scale)

Popular Solutions: - Pinecone (managed) - Weaviate (open source) - Milvus (open source) - Qdrant (open source) - Chroma (lightweight) - pgvector (PostgreSQL extension)

Use Cases: - RAG systems - Semantic search - Recommendation engines - Image similarity

Examples

Pinecone storing document embeddings for a customer support chatbot.

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