head to head · open source
langchain vs R2R
langchain has 148,892 GitHub stars, 25,031 forks, 492 open issues and last shipped yesterday. R2R has 8,055 stars, 650 forks, 126 open issues and last shipped 12 months ago. langchain leads on adoption by 1,748% (148,892 vs 8,055 stars). langchain is written in Python under MIT; R2R is written in Python under MIT. langchain has attracted 17% as many forks as stars, R2R 8%. langchain was the more recently maintained of the two, and both are self-hostable with no licence fee.
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
| langchain | R2R | |
|---|---|---|
| GitHub stars | ★ 149K | ★ 8.1K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2025-11-07 |
| Forks | ⑂ 25K | ⑂ 650 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick langchain if
- You weight community size — 149K 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 langchain
The agent engineering platform. LangChain is a framework for building agents and LLM powered applications. It helps you chain together interoperable components and third party integrations to simplify AI application development — all while future proofing decisions as the underlying technology evolves. [!TIP] Just getting started? Check out Deep Agents — a higher level package built on LangChain for agents that have built in capabilities for common usage patterns such as planning, subagents, file system usage, and more. Quickstart If you're looking for more advanced customization or agent orchestration, check…
read the full langchain 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 langchain or R2R more popular?
langchain has 148,892 GitHub stars and R2R has 8,055. langchain has the larger community by that measure.
Are langchain and R2R free?
Both are open source. langchain is licensed under MIT and R2R under MIT. Neither carries a licence fee.
What is the difference between langchain and R2R?
langchain 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, langchain or R2R?
Choose langchain if you want the larger community (148,892 stars) or its MIT licence terms. Choose R2R if its feature set, stack or MIT licence fits better. Both are self-hostable.