#1 · by Pinecone
Pinecone Vector Database
Serverless vector database for semantic search and RAG.
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Vector databases for AI search and RAG
Vector databases store embeddings so AI apps can find relevant content by meaning. They power search and RAG systems.
SARVO lists 4 tools for this task. Tools with no implementation partner are sold directly by the vendor, and SARVO can connect you with them. Ask SARVO to match your exact need.
Tools to consider
#2 · by Weaviate
Weaviate Cloud
Managed Weaviate vector database.
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#3 · by Qdrant
Qdrant Cloud
Managed Qdrant vector search.
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1 implementation partnerView partners →
What to check before you choose
- Managed service or self-hosted?
- Scale and speed at your data size.
- Filtering, security and access control.
- Fit with your existing database.
SARVO does not certify tools. Verify security and data terms with each vendor.
Compare tools
Pinecone Vector Database vs Weaviate CloudPinecone Vector Database vs Qdrant CloudPinecone Vector Database vs MongoDB Atlas Vector SearchWeaviate Cloud vs Qdrant CloudWeaviate Cloud vs MongoDB Atlas Vector SearchQdrant Cloud vs MongoDB Atlas Vector SearchPinecone Vector Database alternativesWeaviate Cloud alternativesQdrant Cloud alternativesMongoDB Atlas Vector Search alternatives
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Frequently asked questions
What is RAG?
Retrieval-augmented generation: the AI looks up your documents before answering.
Which vector database should I pick?
Pinecone is fully managed, Weaviate and Qdrant offer open-source options, and MongoDB adds vector search to an existing database.
Do I need one?
For small document sets, a simple search may be enough.