chroma vs llama_index
The two are close in size: 29.2k stars for chroma, 52.0k for llama_index. Over the days we have tracked them chroma moved +3.5% and llama_index +2%, so chroma is growing faster right now.
llama_index leads on context depth and customization. chroma does not take any axis by a clear margin.
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
A data-first RAG framework focused on document agents and agentic OCR with extensive indexing, retrieval, and 300+ integrations.
- Stars
- 52.0k
- Tracked growth
- +2%
- Maturity
- ●●●●●
- Last commit
- 6h ago
- Language
- Python
- License
- MIT
- Cost to run
- Your API key (or optional LlamaParse cloud)
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.
| Axis | chroma | llama_index |
|---|---|---|
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-data ingestion |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Basic filters | ●●●●● Rerankers + filters |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Configurable API | ●●●●● Highly extensible |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Runs locally | ●●●●● Local model support |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring-your-own models | ●●●●● BYO models & keys |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Quick start | ●●●●● Config + API key |
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.
Pick llama_index if…
Document-agent focused — pick LlamaIndex when you need a flexible, extensible RAG/document-agent/OCR framework with strong local model and integration support.
- Context depth: Whole-data ingestion (5/5 against 1/5)
- Customization: Highly extensible (5/5 against 3/5)
What people want from each one
chroma-core/chroma
Hacker News: Chroma: Ubisoft's internal tool used to simulate color-blindness drew 231 points and 86 comments.
run-llama/llama_index
Questions people ask
Is chroma better than llama_index?
llama_index leads on context depth and customization. chroma does not take any axis by a clear margin. 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 llama_index keeps my code private?
chroma: Runs locally (5/5). llama_index: Local model support (5/5).
What does each one cost to run?
chroma: Free to self-host; optional Chroma Cloud hosted service. llama_index: Your API key (or optional LlamaParse cloud).
Full profiles: chroma-core/chroma and run-llama/llama_index. Everything else in RAG & retrieval.