Vector Database Finder
Answer 4 quick questions and we'll recommend the best vector database for your project. Powered by data from 20+ databases.
What scale do you need?
How many vectors will you store?
Frequently Asked Questions
Which vector database should I use for RAG?
For RAG (Retrieval-Augmented Generation), the best choice depends on your scale and deployment preferences. Pinecone and Weaviate are popular for managed RAG pipelines, while Qdrant and Milvus offer high performance for self-hosted setups. pgvector is great if you already use PostgreSQL.
What is the best vector database for beginners?
ChromaDB is the easiest to get started with — it embeds directly in your Python app with zero configuration. For a managed experience, Pinecone offers a simple API with no infrastructure to manage. Supabase Vector is ideal if you want vectors alongside a full-stack backend.
How do I choose between cloud and self-hosted vector databases?
Choose cloud/managed (Pinecone, Zilliz) if you want zero ops and auto-scaling. Choose self-hosted (Qdrant, Milvus, Weaviate) if you need data sovereignty, cost control, or customization. Hybrid options like Milvus offer both.
Can I use my existing database for vector search?
Yes. PostgreSQL (via pgvector), MongoDB (Atlas Vector Search), Elasticsearch, Redis, and others now support vector search natively. This avoids adding new infrastructure but may have performance trade-offs at large scale.