head to head · open source
llama_index vs Laminar
llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. Laminar has 3,265 stars, 239 forks, 116 open issues and last shipped yesterday. llama_index leads on adoption by 1,499% (52,202 vs 3,265 stars). llama_index is written in Python under MIT; Laminar is written in TypeScript under Apache-2.0. llama_index has attracted 16% as many forks as stars, Laminar 7%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (agents), 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 | Laminar | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 3.3K |
| License | MIT | Apache-2.0 |
| Written in | Python | TypeScript |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 8.2K | ⑂ 239 |
| 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 Laminar if
- You want the Laminar feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches TypeScript
- You evaluated both and Laminar 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 Laminar
Laminar is an open source observability platform purpose built for AI agents, distributed under the Apache 2.0 license and written primarily in TypeScript. It was built by the team behind Y Combinator's S24 batch and lives in the AI and machine learning infrastructure ecosystem, with a topic list spanning agent observability, LLM evaluation, LLMOps and AIOps. The project ships as a tracing and evaluation stack rather than a general purpose APM tool, and its homepage at laminar.sh hosts both documentation and a managed offering.
read the full Laminar overview →
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Frequently asked questions
Is llama_index or Laminar more popular?
llama_index has 52,202 GitHub stars and Laminar has 3,265. llama_index has the larger community by that measure.
Are llama_index and Laminar free?
Both are open source. llama_index is licensed under MIT and Laminar under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and Laminar?
llama_index is written in Python and Laminar in TypeScript. 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 Laminar?
Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose Laminar if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.