Vector Databases Compared
What vector databases do, when you need one, and how Chroma, Weaviate, Milvus, Qdrant and pgvector stack up against each other.
Redaktion
Vektor-Datenbanken
in KI-Werkzeuge
Datenbanken für Embeddings und semantische Suche.
Glossary
Chroma Vektor-Datenbanken
Chroma (ChromaDB) is an open-source vector database for storing and searching embeddings. It is widely used in RAG systems to retrieve relevant text passages via similarity search and feed them to language models.
Milvus Vektor-Datenbanken
Milvus is an open-source, distributed vector database for fast similarity search over large sets of embeddings. It is licensed under Apache 2.0 within the LF AI & Data Foundation; the main developer is the company Zilliz.
pgvector Vektor-Datenbanken
pgvector is an open-source PostgreSQL extension for vector search — adding embedding columns, distance functions, and ANN indexes (HNSW, IVFFlat) directly to an existing Postgres database.
Pinecone Vektor-Datenbanken
Pinecone is a managed vector database service for RAG and semantic-search workloads — it stores embeddings, answers nearest-neighbour queries, and scales without the user operating the index themselves.
Qdrant Vektor-Datenbanken
Qdrant is an open-source vector database written in Rust — it stores embeddings for semantic search, RAG and recommendation systems and runs locally, on your own cluster or as a managed cloud.
Weaviate Vektor-Datenbanken
Weaviate is an open-source vector database written in Go — it stores objects together with their embeddings, combines semantic and keyword (BM25) search and offers built-in vectorization, RAG and multi-tenancy.