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Chroma vs supavec

Open-source embedding database for building AI apps with retrieval. — versus — Open-source RAG-as-a-service (the Carbon.ai alternative): upload any data source, get vector search and a chat API in minutes — Supabase-based, multi-tenant with RLS, streaming responses.

The curated verdict

Different layers of the same job: Chroma gives you the embedding database and you assemble ingestion, chunking and chat around it; Supavec sells the whole assembled slice as one API.

Chromasupavec
Stars29k1.1k
Forks2.4k102
LanguagePythonTypeScript
LicenseApache-2.0Apache-2.0
Last activity2 days ago6 months ago
Topicsrag, memoryrag
Curated connections82

Chroma — the curator's take

Open-source embedding database for building AI apps with retrieval.

supavec — the curator's take

The API-first take on RAG: POST a file, query a /chat endpoint, done — with genuinely production-minded internals (row-level security for tenant isolation, batched embeddings cutting OpenAI cost ~65%, Redis sliding-window rate limits, request tracing). Use it when you want RAG behind an API for your product without assembling the pipeline yourself. Know the shape: it's an open-core SaaS — usage-tiered billing on the cloud version, and self-hosting means running the Next.js + Supabase + Upstash stack yourself with docs that assume you'll read the code. For a self-contained enterprise RAG product with a UI, MaxKB; for just the vector store, Chroma.