Pinecone vs Rivestack

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Pinecone RAG	Rivestack RAG
Tagline	Managed vector database for production-scale similarity search.	Managed Postgres with pgvector on dedicated NVMe, pitched as a cheaper RAG backend than Pinecone or Supabase.
Category	RAG	RAG
Pricing	Freemium· Free starter; serverless pay-as-you-go from $0.33/1M reads	Freemium· Free shared tier; Solo $15/mo, Starter $35, Growth $59, Scale $99 (EU Central)
Model	Hosted vector DB (not an LLM)	OpenAI embeddings (auto-embeddings)
Editorial score	8.8 / 10	—
Use cases	managed vector DBproduction RAG	rag-backendvector-searchsemantic-searchmanaged-postgresembeddings-storage
Pros	Zero ops Low query latency Mature SDKs Serverless pricing is now sensible	Dedicated NVMe Postgres is genuinely fast for pgvector HNSW workloads Cheaper than Pinecone at small/medium scale One database for vectors and relational data, no sync layer Auto-embeddings on insert removes a pipeline step Standard Postgres wire protocol, works with any existing driver
Cons	Costs scale with vector count Less flexible than self-hosted	EU Central only at launch limits latency for US/APAC apps Tied to OpenAI for the auto-embeddings convenience feature Scale tier caps at ~1M vectors, not a fit for billion-scale corpora Younger service with thinner track record than Supabase or Neon
Website	www.pinecone.io	rivestack.io

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