Vector Database Comparison Tool
Compare vector databases for your AI application. Input your requirements and get a scored recommendation across Pinecone, Weaviate, Qdrant, Milvus, and pgvector.
- Free Comparison
- 5 Vector DBs
- Scored Recommendations
Vector Database Comparison Tool
Frequently asked questions
What is a vector database?
A vector database stores high-dimensional numerical representations (embeddings) of data and enables fast similarity search. They power AI features like semantic search, recommendation systems, and RAG pipelines.
When should I use pgvector vs a dedicated vector database?
Use pgvector when you already run PostgreSQL, have under 5-10 million vectors, and moderate query throughput. Switch to a dedicated vector DB when you need higher QPS, advanced filtering, or multi-tenant isolation.
How much does a vector database cost?
Costs range from $50/month for pgvector on existing Postgres to $500-5,000/month for managed services at moderate scale. At enterprise scale (100M+ vectors), costs can reach $10,000-50,000/month.
Can I migrate between vector databases?
Yes, but it requires re-indexing. Export vectors as arrays, transform metadata to the target schema, and import. Expect 1-4 hours for 10M vectors. Keep embedding generation code separate from DB-specific code.
Need Help with Vector Database Architecture?
We help teams choose, deploy, and scale vector databases for production AI applications. Book a discovery call to discuss your requirements.
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