dagster vs llm-app

Common questions

What is the difference between dagster and llm-app?

dagster: An orchestration platform for data assets. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. See the comparison table for live GitHub stats and shared categories.

When should I choose dagster over llm-app?

Choose dagster over llm-app when dagster is primarily Python; llm-app is Jupyter Notebook; License: dagster is Apache-2.0, llm-app is MIT; Tags unique to dagster: data-engineering, data-orchestrator, etl, mlops; When your project requires an Apache-2.0 licensed tool allowing broader reuse and modification of code.

When should I choose llm-app over dagster?

Choose llm-app over dagster when llm-app is primarily Jupyter Notebook; dagster is Python; License: llm-app is MIT, dagster is Apache-2.0; Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.; Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.; Tags unique to llm-app: chatbot, hugging-face, llm, llm-local; Also covers Inference & Serving, Model Training; When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti.

When should I avoid dagster?

If you are restricted to proprietary or non-open-source licenses, as Dagster's Apache-2.0 might not align with compliance requirements. In environments where Python is not a preferred language, considering Dagster requires good knowledge of the Python ecosystem. For teams that do not require or benefit from extensive documentation and hands-on tutorials for onboarding. If specific features or integrations crucial to your workflow are found lacking in comparison to competitors.

When should I avoid llm-app?

Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities.

Is dagster or llm-app more popular on GitHub?

llm-app has more GitHub stars (58,920 vs 16,144). Stars measure visibility, not whether either tool fits your constraints.

Are dagster and llm-app open source?

Yes - both are open-source projects on GitHub (dagster: Apache-2.0, llm-app: MIT).

Where can I find alternatives to dagster or llm-app?

GraphCanon lists graph-backed alternatives at dagster alternatives and llm-app alternatives (dagster markdown twin, llm-app markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, dagster or llm-app?

dagster: Very active. llm-app: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for dagster and llm-app?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dagster trust report; llm-app trust report.