What is Vector Database?
TL;DR
A database specialized for storing and searching high-dimensional vector data. A foundational technology for RAG.
Vector Database: Definition & Explanation
A vector database is a specialized database designed to efficiently store high-dimensional vectors generated by embeddings and perform fast similarity searches. It stores text, images, audio, and other data in vector form, enabling instant retrieval of 'semantically similar' items. Vector databases are essential infrastructure for building RAG (Retrieval-Augmented Generation) systems — documents are converted into embeddings and stored in the database, allowing rapid retrieval of the most relevant information for a user's query. Leading products include Pinecone, Weaviate, Chroma, Milvus, Qdrant, and pgvector. Combined with AI frameworks like LangChain and Dify, vector databases power enterprise knowledge base search, recommendation systems, and image similarity search. Their defining advantage is enabling 'semantic' search — something that traditional relational databases struggle with.