head to head · open source
llama_index vs great_expectations
llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. great_expectations has 11,797 stars, 1,850 forks, 42 open issues and last shipped yesterday. llama_index leads on adoption by 343% (52,202 vs 11,797 stars). llama_index is written in Python under MIT; great_expectations is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, great_expectations 16%. llama_index 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.
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Side by side
| llama_index | great_expectations | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 12K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 8.2K | ⑂ 1.9K |
| 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 great_expectations if
- You want the great_expectations 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 great_expectations 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 great_expectations
Great Expectations, referred to in its own documentation as GX Core, is an open source Python library for validating and documenting the quality of data. It lives in the Python data ecosystem and is published under the Apache 2.0 license. The project has been in development for roughly nine years and carries about 11,794 stars with 1,848 forks, which places it among the longer running tools in the data quality space. Its central concept is the Expectation: an expressive, extensible unit test written against a dataset rather than against application code.
read the full great_expectations overview →
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Frequently asked questions
Is llama_index or great_expectations more popular?
llama_index has 52,202 GitHub stars and great_expectations has 11,797. llama_index has the larger community by that measure.
Are llama_index and great_expectations free?
Both are open source. llama_index is licensed under MIT and great_expectations under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and great_expectations?
llama_index is written in Python and great_expectations 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 great_expectations?
Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose great_expectations if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.