Comparison
dagster vs docetl
Verdict
Pick dagster if dagster is an open-source orchestration platform developed in Python for managing and observing data pipelines and workflows; pick docetl if docetl is an agentic system that employs large language models for data processing and ETL operations, specifically suited to handle unstructured document analysis tasks.
Markdown twin · dagster alternatives · docetl alternatives
GraphCanon updated Sep 15, 2026
16views this month
Trust & integrity
| Signal | dagster | docetl |
|---|---|---|
| Maintenance | Very active (2d since push) As of Sep 14, 2026 · github_public_v1 | Active (9d since push) As of Sep 15, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 14, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 15, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- dagster
- An orchestration platform for data assets
- docetl
- A system for agentic LLM-powered data processing and ETL
Stars
- dagster
- 16k
- docetl
- 4.1k
Forks
- dagster
- 2.3k
- docetl
- 443
Open issues
- dagster
- 2.6k
- docetl
- 45
Language
- dagster
- Python
- docetl
- Python
Adopt for
- dagster
- Dagster is an open-source orchestration platform developed in Python for managing and observing data pipelines and workflows.
- docetl
- Docetl is an agentic system that employs large language models for data processing and ETL operations, specifically suited to handle unstructured document analysis tasks.
Persona
- dagster
- -
- docetl
- -
Runtime
- dagster
- -
- docetl
- -
License
- dagster
- Apache-2.0
- docetl
- MIT
Last pushed
- dagster
- Sep 11, 2026
- docetl
- Sep 5, 2026
Categories
- dagster
- Data & Retrieval, Evaluation & Observability
- docetl
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- dagster
- Very active (96%)
- docetl
- Active (82%)
Days since push
- dagster
- 2d
- docetl
- 9d
Open issues (now)
- dagster
- 2.6k
- docetl
- 45
Stars delta
- dagster
- +195 (30d)
- docetl
- +131 (30d)
Open issues delta
- dagster
- -9 (30d)
- docetl
- +3 (30d)
Full report
- dagster
- Trust report
- docetl
- Trust report
Shared compatibility
- Python · dagster: Python runtime · docetl: Python runtime
Choose dagster if…
- License: dagster is Apache-2.0, docetl is MIT.
- Tags unique to dagster: data-engineering, data-orchestrator, mlops, workflow.
- Also covers Evaluation & Observability.
- When your project requires an Apache-2.0 licensed tool allowing broader reuse and modification of code.
When NOT to use 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.
Choose docetl if…
- License: docetl is MIT, dagster is Apache-2.0.
- Tags unique to docetl: agents, data, document-analysis, llm.
- Also covers AI Agents.
- docetl ships Docker support for self-hosted deployment.
- When you require integration with any LLM provider through API keys like OPENAI_API_KEY.
When NOT to use docetl
- If your project strictly requires low-latency processing for real-time applications, as Docetl's agentic approach might introduce higher latency due to backend API calls.
- In scenarios where the document datasets are predominantly structured or semi-structured, making traditional ETL tools more efficient.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (dagster-io/dagster) · observed Sep 14, 2026
- GitHub forks (dagster-io/dagster) · observed Sep 14, 2026
- Last push (dagster-io/dagster) · observed Sep 11, 2026
- License file (Apache-2.0) · observed Sep 14, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (ucbepic/docetl) · observed Sep 15, 2026
- GitHub forks (ucbepic/docetl) · observed Sep 15, 2026
- Last push (ucbepic/docetl) · observed Sep 5, 2026
- License file (MIT) · observed Sep 15, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: dagster 16k · docetl 4.1k (synced Sep 14, 2026).
Common questions
- What is the difference between dagster and docetl?
- dagster: An orchestration platform for data assets. docetl: A system for agentic LLM-powered data processing and ETL. See the comparison table for live GitHub stats and shared categories.
- When should I choose dagster over docetl?
- Choose dagster over docetl when License: dagster is Apache-2.0, docetl is MIT; Tags unique to dagster: data-engineering, data-orchestrator, mlops, workflow; Also covers Evaluation & Observability; When your project requires an Apache-2.0 licensed tool allowing broader reuse and modification of code.
- When should I choose docetl over dagster?
- Choose docetl over dagster when License: docetl is MIT, dagster is Apache-2.0; Tags unique to docetl: agents, data, document-analysis, llm; Also covers AI Agents; docetl ships Docker support for self-hosted deployment; When you require integration with any LLM provider through API keys like OPENAI_API_KEY.
- 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 docetl?
- If your project strictly requires low-latency processing for real-time applications, as Docetl's agentic approach might introduce higher latency due to backend API calls. In scenarios where the document datasets are predominantly structured or semi-structured, making traditional ETL tools more efficient.
- Is dagster or docetl more popular on GitHub?
- dagster has more GitHub stars (16,144 vs 4,092). Stars measure visibility, not whether either tool fits your constraints.
- Are dagster and docetl open source?
- Yes - both are open-source projects on GitHub (dagster: Apache-2.0, docetl: MIT).
- Where can I find alternatives to dagster or docetl?
- GraphCanon lists graph-backed alternatives at dagster alternatives and docetl alternatives (dagster markdown twin, docetl 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 docetl?
- dagster: Very active. docetl: Active. 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 docetl?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dagster trust report; docetl trust report.