Chroma
Open-source embedding database — the fast path from prototype to local vector search
Chroma is an open-source vector store designed to run in-memory or on disk with zero infrastructure setup. It provides a simple Python and TypeScript client, native LangChain and LlamaIndex integrations, and supports metadata filtering. Chroma Cloud offers a managed option for teams ready to move beyond local development.
Local development, prototyping, and small-to-medium production deployments where you want full control over your vector store without the cost of a managed service.
Solo builders and small teams who want to start building immediately without provisioning cloud infrastructure. Zero-cost for self-hosted; Chroma Cloud is paid.
Agent Architecture Fit
Chroma fills the same retrieval memory slot in a blueprint as Pinecone — but is the preferred choice during the build phase of any agent. Its in-process mode means zero setup: your agent can start embedding and retrieving without any external service. Migrate to a managed store like Pinecone when the collection grows beyond what local storage can handle or when you need multi-region availability.
LangChain
The most widely-adopted framework for building LLM-powered applications and agents
LlamaIndex
The data framework for building LLM applications over custom knowledge sources
Supabase
Open-source Firebase alternative — Postgres, auth, storage, and pgvector in one platform
Next step
Your agent starts with a blueprint.
A blueprint tells you which tools to use, where they fit, and how they connect — before you write a line of code.
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