chroma vs ragflow

ragflow is much bigger: 90.1k stars against 29.2k. Over the days we have tracked them chroma moved +3.5% and ragflow +5.7%, so ragflow is growing faster right now.

They split the axes: chroma leads on setup ease, ragflow on context depth.

Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.

Where they stand today

Provides a minimal, 4-function client API for fast in-memory prototyping plus an optional hosted Chroma Cloud for production-ready vector search.

Stars
29.2k
Tracked growth
+3.5%
Maturity
Last commit
12h ago
Language
Rust
License
Apache-2.0
Cost to run
Free to self-host; optional Chroma Cloud hosted service

Combines a production-grade RAG engine with agent orchestration and template-based document understanding to provide an agentic context layer for LLMs.

Stars
90.1k
Tracked growth
+5.7%
Maturity
Last commit
8h ago
Language
Go
License
Apache-2.0
Cost to run
Your API key (paid LLMs); self-host or use cloud
0%+6%90 tracked days
chroma-core/chromainfiniflow/ragflow

Six axes, head to head

Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.

Axischromaragflow
Context depth
How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository.
No repo context
Whole-repo analysis
Noise control
How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only.
Basic filters
Re-ranking & citations
Customization
How far it bends to your team: custom rules, prompts, style guides, per-path config.
Configurable API
Config files & templates
Privacy
Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only.
Runs locally
Self-hostable
Model freedom
Whether you can point it at any provider, or it is wired to one.
Bring-your-own models
Bring-your-own key
Setup ease
What it takes to get a first useful run out of it.
Quick start
Multi-service deploy

Which one to pick

Pick chroma if…

Easy setup — pip install chromadb and use a simple 4-function API to run an in-memory vector DB for rapid prototyping, with an optional hosted cloud when you need it.

  • Setup ease: Quick start (5/5 against 1/5)
Runs in cli, web-app. Works with byok.

Pick ragflow if…

Self-hostable — choose RAGFlow when you need a production-ready, agentic RAG platform with template-based ingestion, grounded citations, and configurable LLM/embedding providers.

  • Context depth: Whole-repo analysis (5/5 against 1/5)
Runs in web-app. Works with byok, openai, gemini.

What people want from each one

Questions people ask

Is chroma better than ragflow?

They split the axes: chroma leads on setup ease, ragflow on context depth. chroma is worth picking when easy setup — pip install chromadb and use a simple 4-function API to run an in-memory vector DB for rapid prototyping, with an optional hosted cloud when you need it.

Which of chroma and ragflow keeps my code private?

chroma: Runs locally (5/5). ragflow: Self-hostable (4/5).

What does each one cost to run?

chroma: Free to self-host; optional Chroma Cloud hosted service. ragflow: Your API key (paid LLMs); self-host or use cloud.

Full profiles: chroma-core/chroma and infiniflow/ragflow. Everything else in RAG & retrieval.