chroma vs PageIndex

The two are close in size: 29.2k stars for chroma, 35.5k for PageIndex. Over the days we have tracked them chroma moved +3.5% and PageIndex +8.7%, so PageIndex is growing faster right now.

They split the axes: chroma leads on setup ease, PageIndex 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

Vectorless, reasoning-based hierarchical retrieval that builds a human-like table-of-contents tree for traceable, context-aware RAG without vector DBs or chunking.

Stars
35.5k
Tracked growth
+8.7%
Maturity
Last commit
3h ago
Language
Python
License
MIT
Cost to run
Uses your LLM API key (e.g. OpenAI); cloud service may be paid.
0%+9%90 tracked days
chroma-core/chromaVectifyAI/PageIndex

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.

AxischromaPageIndex
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
Basic filters/config
Customization
How far it bends to your team: custom rules, prompts, style guides, per-path config.
Configurable API
Config file options
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
Setup ease
What it takes to get a first useful run out of it.
Quick start
API key + install

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 3/5)
Runs in cli, web-app. Works with byok.

Pick PageIndex if…

Vectorless, reasoning-based retrieval — pick PageIndex when you need traceable, explainable, context-aware answers from long professional documents without a vector DB.

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

What people want from each one

Questions people ask

Is chroma better than PageIndex?

They split the axes: chroma leads on setup ease, PageIndex 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 PageIndex keeps my code private?

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

What does each one cost to run?

chroma: Free to self-host; optional Chroma Cloud hosted service. PageIndex: Uses your LLM API key (e.g. OpenAI); cloud service may be paid..

Full profiles: chroma-core/chroma and VectifyAI/PageIndex. Everything else in RAG & retrieval.