What is Vector Database?
A database optimized for storing and searching AI embeddings at scale.
Definition
A vector database is a specialized database designed to store, index, and query high-dimensional vectors (embeddings). Unlike traditional databases that search by exact matches, vector databases find the most similar vectors using mathematical distance calculations. They are essential for RAG systems, semantic search, and recommendation engines.
💡 Example
Pinecone, Weaviate, and Chroma are popular vector databases. A company might store embeddings of all their documentation in a vector database, then query it with a user question to find the most relevant documents for a RAG system.
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What is Vector Database?
A vector database is a specialized database designed to store, index, and query high-dimensional vectors (embeddings). Unlike traditional databases that search by exact matches, vector databases find the most similar vectors using mathematical distance calculations. They are essential for RAG systems, semantic search, and recommendation engines.
How does Vector Database work in practice?
Pinecone, Weaviate, and Chroma are popular vector databases. A company might store embeddings of all their documentation in a vector database, then query it with a user question to find the most relevant documents for a RAG system.