Rivestack
by Community
Managed pgvector on dedicated PostgreSQL with NVMe storage. 2,000 QPS at sub-4ms p50, from $35/month, migration help from Supabase, Neon, Pinecone, and self-hosted.
OSS
Rivestack
Added 1 June 2026
Overview
Rivestack provides managed pgvector on dedicated PostgreSQL servers with NVMe storage. It delivers 2,000 queries per second at under 4ms p50 latency starting at $35 per month. The service offers migration assistance from Supabase, Neon, Pinecone, and self-hosted deployments.
Best for
Best for
Teams needing a dedicated, high-performance managed pgvector database for production vector search and retrieval-augmented generation workloads.
Use cases
- Scaling vector search for production applications
- Migrating vector databases to dedicated PostgreSQL
- Running high-performance RAG pipelines with pgvector
Notes
Rivestack provides managed pgvector on dedicated PostgreSQL servers with NVMe storage. It delivers 2,000 queries per second at under 4ms p50 latency starting at $35 per month. The service offers migration assistance from Supabase, Neon, Pinecone, and self-hosted deployments.
Use cases
- Scaling vector search for production applications
- Migrating vector databases to dedicated PostgreSQL
- Running high-performance RAG pipelines with pgvector
Pros
- Dedicated NVMe storage ensures low latency and consistent performance
- Competitive pricing ($35/month) for a managed dedicated instance
- Migration support reduces friction when switching from other vector platforms
Cons
- Limited to the pgvector extension; no support for alternative vector index types
- Dedicated instance may be overkill for small-scale or low-traffic projects
- No managed scaling beyond a single dedicated server (likely vertical only)
Indexed from awesome-llmops and enriched against its public facts.
Pros
- Dedicated NVMe storage ensures low latency and consistent performance
- Competitive pricing ($35/month) for a managed dedicated instance
- Migration support reduces friction when switching from other vector platforms
Cons
- Limited to the pgvector extension; no support for alternative vector index types
- Dedicated instance may be overkill for small-scale or low-traffic projects
- No managed scaling beyond a single dedicated server (likely vertical only)
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