head to head · open source
llama_index vs LightRAG
llama_index has 52,206 GitHub stars, 8,165 forks, 770 open issues and last shipped today. LightRAG has 39,738 stars, 5,589 forks, 222 open issues and last shipped today. llama_index leads on adoption by 31% (52,206 vs 39,738 stars). llama_index is written in Python under MIT; LightRAG is written in Python under MIT. llama_index has attracted 16% as many forks as stars, LightRAG 14%. llama_index 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
| llama_index | LightRAG | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 40K |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-09-18 | 2026-09-18 |
| Forks | ⑂ 8.2K | ⑂ 5.6K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 52K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick LightRAG if
- You want the LightRAG feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and LightRAG fits your workflow better
About llama_index
LlamaIndex is an MIT licensed, open source Python framework for building agentic applications — retrieval augmented generation systems, agents and multi agent workflows — on top of private documents and data, and it is aimed at AI engineers and teams who need to connect large language models to their own sources of context.
read the full llama_index overview →
About LightRAG
LightRAG is a Python retrieval augmented generation framework, released under the MIT licence and presented in an EMNLP 2025 paper, that builds a knowledge graph over documents so that queries can be answered from both graph structure and vector similarity.
read the full LightRAG overview →
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Frequently asked questions
Is llama_index or LightRAG more popular?
llama_index has 52,206 GitHub stars and LightRAG has 39,738. llama_index has the larger community by that measure.
Are llama_index and LightRAG free?
Both are open source. llama_index is licensed under MIT and LightRAG under MIT. Neither carries a licence fee.
What is the difference between llama_index and LightRAG?
llama_index is written in Python and LightRAG 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, llama_index or LightRAG?
Choose llama_index if you want the larger community (52,206 stars) or its MIT licence terms. Choose LightRAG if its feature set, stack or MIT licence fits better. Both are self-hostable.