Vector Database
A Vector Database is a specialized storage engine designed to store, index, and query high-dimensional vector embeddings efficiently. It enables fast semantic search and similarity matching using algorithms like HNSW or IVF.
Frequently Asked Questions
Why are vector databases needed for AI?▼
Traditional databases index text or numbers. AI models represent concepts as multi-dimensional vectors (embeddings), requiring special indexes to find close vectors quickly.
What are some popular vector databases?▼
Dedicated databases include Pinecone, Milvus, Qdrant, Chroma, and Weaviate, while existing systems like PostgreSQL support vector extensions (pgvector).
Quick Facts
- CategoryData Infrastructure
- Key ApplicationRetrieval-Augmented Generation (RAG), semantic search engines, and real-time recommendation systems.
Coverage Trend12 Weeks
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