Vector databases for AI apps
If you are adding RAG, the database choice is usually: stay on Postgres with pgvector, or buy a specialist (Pinecone, Qdrant, Weaviate). Specialists win on ops and filters at scale. Postgres wins when you already run SQL and do not want another bill. This hub is for that fork, not for picking an LLM.
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Do I need a dedicated vector DB?
Not for a prototype. pgvector on a database you already have is enough until metadata filters, recall, or ops hurt.
Pinecone vs Qdrant vs Weaviate?
Pinecone is hosted-first. Qdrant and Weaviate you can self-host. Read the current pricing and SLAs on each page. We will not rank them from memory.
Is this the same as a model hub?
No. Models generate embeddings. This category stores and searches them.
All Vector databases for AI apps tools (13)
Open any tool below for details, features, and pricing.
ElasticsearchElasticsearch is Elastic's distributed search and analytics…
FaissMeta ANN library. A library, not a hosted vector DB or marke…
MilvusMilvus is an open-source distributed vector database; its ma…
MySQLMySQL is Oracle's open source relational database: GPLv2 Com…
NeonServerless Postgres. Auth/storage/functions are beta extras.
PostgreSQLPostgreSQL is an open-source object-relational database rele…
PGVectorPostgres vector extension. Not a Faiss wrapper. No hosted do…
PineconePinecone is a managed vector database with indexes, inferenc…
QdrantQdrant is an open-source, Apache-2.0 vector search engine wi…
SupabaseOpen Firebase alternative. Auth/storage shipped; not still-i…
UpstashUpstash is a serverless data platform centered on Redis, wit…
ValdVald is a Kubernetes-oriented distributed approximate neares…
VespaOSS search+vector engine. Cloud has a free trial; unit table…