head to head · open source
llama_index vs dagster
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. dagster has 16,364 stars, 2,395 forks, 2,589 open issues and last shipped 4 days ago. llama_index leads on adoption by 223% (52,779 vs 16,364 stars). llama_index is written in Python under MIT; dagster is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, dagster 15%. dagster 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 | dagster | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 16K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-10-26 | 2026-10-30 |
| Forks | ⑂ 8.5K | ⑂ 2.4K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 53K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick dagster if
- You want the dagster 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 dagster fits your workflow better
About llama_index
🗂️ LlamaIndex (OSS Framework) 🦙 [!NOTE] The current focus of LlamaIndex is to build the best AI powered engine for document parsing and extraction. LlamaParse is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. LiteParse represents our efforts to build the best free, fast, cheap text parser in the market. ParseBench and ExtractBench represent our commitment towards open benchmarking for parsing and extraction. The company itself has undergone an evolution since when this OSS framework first launched 3 years ago in 2023. Since the early days, the framework has consisted of a…
read the full llama_index overview →
About dagster
Dagster is a cloud native data pipeline orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best in class testability. It is designed for developing and maintaining data assets , such as tables, data sets, machine learning models, and reports. With Dagster, you declare—as Python functions—the data assets that you want to build. Dagster then helps you run your functions at the right time and keep your assets up to date. Here is an example of a graph of three assets defined in Python: The graph loaded into Dagster's web UI: Dagster is…
read the full dagster overview →
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Frequently asked questions
Is llama_index or dagster more popular?
llama_index has 52,779 GitHub stars and dagster has 16,364. llama_index has the larger community by that measure.
Are llama_index and dagster free?
Both are open source. llama_index is licensed under MIT and dagster under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and dagster?
llama_index is written in Python and dagster 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 dagster?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose dagster if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.