Best vector database providers in 2026

A vector database stores embeddings. These are numerical representations of text, images, or other data. It finds the stored items closest in meaning to a query. Retrieval-augmented generation (RAG), semantic search, and recommendations all depend on this kind of similarity search.

Vector databases come in two broad forms. Some are dedicated systems built only for vector search. Others, like Postgres with the pgvector extension, add vector search to a general-purpose database. The right choice depends on your data volume, how much infrastructure you want to run, and whether your vectors need to live next to your other application data.

Supabase

Supabase is a Postgres development platform. It runs vector search through the pgvector extension, so embeddings are stored in regular tables next to your users, rows, and other data.

Because the vectors sit in Postgres, you can:

• Filter similarity results with ordinary SQL WHERE clauses.
• Apply Row Level Security policies to vector data.
• Combine semantic search with keyword search in a single query.
• Store and query embeddings through the Data API or from Edge Functions.

Supabase is a good fit if you already use Postgres or want one backend for relational data, authentication, storage, and vectors.

Pinecone

Pinecone is a closed-source, managed vector database. Pinecone is a common choice for teams that want vector search with little operational work and great developer experience.

See the Pinecone documentation.

Qdrant

Qdrant is an open-source vector database. You can self-host it, or use Qdrant Cloud as a managed service. Qdrant Cloud has a Free forever tier, which makes it a good choice for prototyping.

See the Qdrant documentation.

Weaviate

Weaviate is an open-source vector database. You can self-host it, or use Weaviate Cloud as a managed service. Weaviate Cloud has a free tier, which makes it a good choice for prototyping.

See the Weaviate documentation.

Milvus

Milvus is an open-source vector database designed for large-scale workloads. You can run it yourself, or use a managed Milvus service such as Zilliz Cloud. It fits teams that care about performance and availability.

See the Milvus documentation.

Choosing a provider

• If you already run Postgres or want one backend for everything, choose Supabase. It keeps vectors next to your relational data, auth, and storage.
• If you want a fully managed vector service and a provider known for developer experience, choose Pinecone.
• If you want open source, but a managed cloud offering with a free tier, choose Qdrant or Weaviate.
• If you expect very large collections and performance is the most important consideration for you, choose Milvus.