head to head · open source

llama_index vs dagster

llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. dagster has 16,169 stars, 2,294 forks, 2,589 open issues and last shipped yesterday. llama_index leads on adoption by 223% (52,202 vs 16,169 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 14%. 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.

llama_index ★ 52K dagster ★ 16K category AI & Machine Learning

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Side by side

llama_index dagster
GitHub stars ★ 52K ★ 16K
License MIT Apache-2.0
Written in Python Python
Last push 2026-09-17 2026-09-17
Forks ⑂ 8.2K ⑂ 2.3K
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

full llama_index profile →

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

full dagster profile →

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 dagster

Dagster is a cloud native data pipeline orchestrator written in Python and released under the Apache 2.0 licence, built for data engineers, data scientists, and machine learning teams who declare the tables, data sets, models, and reports their pipelines should produce and need those assets tested, observable, and kept up to date from local development through production.

read the full dagster overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

llama_index vs Ollama llama_index vs llama.cpp llama_index vs vllm llama_index vs GPT4All llama_index vs LocalAI llama_index vs PageIndex llama_index vs Langfuse llama_index vs cognee llama_index vs taipy llama_index vs zvec llama_index vs langchain4j llama_index vs txtai

Frequently asked questions

Is llama_index or dagster more popular?

llama_index has 52,202 GitHub stars and dagster has 16,169. 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 (52,202 stars) or its MIT licence terms. Choose dagster if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.