head to head · open source
llama_index vs haystack
llama_index has 52,206 GitHub stars, 8,165 forks, 770 open issues and last shipped today. haystack has 26,534 stars, 3,144 forks, 143 open issues and last shipped today. llama_index leads on adoption by 97% (52,206 vs 26,534 stars). llama_index is written in Python under MIT; haystack is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, haystack 12%. 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 (agents, framework), 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 | haystack | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 27K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-18 | 2026-09-18 |
| Forks | ⑂ 8.2K | ⑂ 3.1K |
| 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 haystack if
- You want the haystack feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and haystack 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 haystack
Haystack is an open source AI orchestration framework written in Python under the Apache 2.0 licence, for building context engineered, production ready large language model applications as modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation, and it is aimed at developers and teams building scalable agents, retrieval augmented generation, multimodal applications, semantic search, question answering, and conversational systems.
read the full haystack overview →
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Frequently asked questions
Is llama_index or haystack more popular?
llama_index has 52,206 GitHub stars and haystack has 26,534. llama_index has the larger community by that measure.
Are llama_index and haystack free?
Both are open source. llama_index is licensed under MIT and haystack under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and haystack?
llama_index is written in Python and haystack 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 haystack?
Choose llama_index if you want the larger community (52,206 stars) or its MIT licence terms. Choose haystack if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.