head to head · open source
graphrag vs R2R
graphrag has 36,547 GitHub stars, 3,871 forks, 47 open issues and last shipped 3 days ago. R2R has 8,057 stars, 651 forks, 126 open issues and last shipped 12 months ago. graphrag leads on adoption by 354% (36,547 vs 8,057 stars). graphrag is written in Python under MIT; R2R is written in Python under MIT. graphrag has attracted 11% as many forks as stars, R2R 8%. graphrag was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (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.
← all 20902 open source comparisons
Side by side
| graphrag | R2R | |
|---|---|---|
| GitHub stars | ★ 37K | ★ 8.1K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2025-11-07 |
| Forks | ⑂ 3.9K | ⑂ 651 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick graphrag if
- You weight community size — 37K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick R2R if
- You want the R2R feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and R2R fits your workflow better
About graphrag
GraphRAG [!WARNING] GraphRAG is a research project that explores the functional use of graphs to form a targeted context for question answering. Since our first release in July 2024 the capabilities of frontier models have changed dramatically, and our portfolio of research projects has diversified to match. This project is largely in maintenance mode, and won't be accepting new PRs or implementing new features. We'll perform bug fixes and dependency updates as appropriate, particularly to address CVEs as they arise. 👉 Microsoft Research Blog Post 👉 Read the docs 👉 GraphRAG Arxiv Overview The GraphRAG project…
read the full graphrag overview →
About R2R
The most advanced AI retrieval system. Agentic Retrieval Augmented Generation (RAG) with a RESTful API. Docs · Report Bug · Feature Request · Discord About R2R is an advanced AI retrieval system supporting Retrieval Augmented Generation (RAG) with production ready features. Built around a RESTful API, R2R offers multimodal content ingestion, hybrid search, knowledge graphs, and comprehensive document management. R2R also includes a Deep Research API , a multi step reasoning system that fetches relevant data from your knowledgebase and/or the internet to deliver richer, context aware answers for complex queries…
More in AI & Machine Learning
Related comparisons
More AI Development Platforms projects
Compare either of these against the rest of the AI Development Platforms field.
Frequently asked questions
Is graphrag or R2R more popular?
graphrag has 36,547 GitHub stars and R2R has 8,057. graphrag has the larger community by that measure.
Are graphrag and R2R free?
Both are open source. graphrag is licensed under MIT and R2R under MIT. Neither carries a licence fee.
What is the difference between graphrag and R2R?
graphrag is written in Python and R2R 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 R2R?
Choose graphrag if you want the larger community (36,547 stars) or its MIT licence terms. Choose R2R if its feature set, stack or MIT licence fits better. Both are self-hostable.