head to head · open source
graphrag vs PageIndex
graphrag has 36,022 GitHub stars, 3,795 forks, 47 open issues and last shipped 2 days ago. PageIndex has 35,696 stars, 3,147 forks, 103 open issues and last shipped yesterday. graphrag leads on adoption by 1% (36,022 vs 35,696 stars). graphrag is written in Python under MIT; PageIndex is written in Python under MIT. graphrag has attracted 11% as many forks as stars, PageIndex 9%. PageIndex was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (llm, rag), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| graphrag | PageIndex | |
|---|---|---|
| GitHub stars | ★ 36K | ★ 36K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-09-16 | 2026-09-17 |
| Forks | ⑂ 3.8K | ⑂ 3.1K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick graphrag if
- You weight community size — 36K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick PageIndex if
- You want the PageIndex feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and PageIndex fits your workflow better
About graphrag
GraphRAG is a modular, Python based, MIT licensed data pipeline and transformation suite from Microsoft Research that uses large language models to extract structured data from unstructured text, then exploits the resulting knowledge graph to form targeted context for question answering over private data.
read the full graphrag overview →
About PageIndex
PageIndex is a vectorless, reasoning based retrieval augmented generation engine written in Python and released under the MIT license. It lives in the AI and machine learning infrastructure ecosystem, with topics spanning RAG, information retrieval, LLM reasoning, context engineering, and agentic AI. Instead of building a vector index, PageIndex generates a hierarchical tree index for each document and then lets a large language model reason its way through that tree, in the same way a human expert turns to the right section of a long report. The project ships as a Python SDK, a hosted cloud service, and a docume…
read the full PageIndex overview →
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Frequently asked questions
Is graphrag or PageIndex more popular?
graphrag has 36,022 GitHub stars and PageIndex has 35,696. graphrag has the larger community by that measure.
Are graphrag and PageIndex free?
Both are open source. graphrag is licensed under MIT and PageIndex under MIT. Neither carries a licence fee.
What is the difference between graphrag and PageIndex?
graphrag is written in Python and PageIndex in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, graphrag or PageIndex?
Choose graphrag if you want the larger community (36,022 stars) or its MIT licence terms. Choose PageIndex if its feature set, stack or MIT licence fits better. Both are self-hostable.