Comparison
kedro vs ploomber
Verdict
Pick kedro if kedro is ideal for productionizing data science projects through its emphasis on software engineering discipline within the Python environment; pick ploomber if ploomber is a Python-based tool that specializes in iterative development and deployment of data pipelines, supporting Jupyter notebooks and integrating smoothly with popular IDEs like PyCharm and VSCode.
Markdown twin · kedro alternatives · ploomber alternatives
GraphCanon updated 3w
Trust & integrity
| Signal | kedro | ploomber |
|---|---|---|
| Maintenance | Very active (1d since push) As of 3w · github_public_v1 | Archived (430d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- kedro
- Toolbox for production-ready data science
- ploomber
- The fastest way to build data pipelines. Develop iteratively, deploy anywhere.
Stars
- kedro
- 11k
- ploomber
- 3.6k
Forks
- kedro
- 1.1k
- ploomber
- 243
Open issues
- kedro
- 163
- ploomber
- 110
Language
- kedro
- Python
- ploomber
- Python
Adopt for
- kedro
- Kedro is ideal for productionizing data science projects through its emphasis on software engineering discipline within the Python environment.
- ploomber
- Ploomber is a Python-based tool that specializes in iterative development and deployment of data pipelines, supporting Jupyter notebooks and integrating smoothly with popular IDEs like PyCharm and VSCode.
Persona
- kedro
- -
- ploomber
- -
Runtime
- kedro
- -
- ploomber
- -
License
- kedro
- Apache-2.0
- ploomber
- Ploomber operates under the Apache License 2.0 which allows free use, modification and distribution, provided that any redistributed code includes an acknowledgement of the original license.
Last pushed
- kedro
- Aug 1, 2026
- ploomber
- May 29, 2025
Categories
- kedro
- Data & Retrieval, Developer Tools
- ploomber
- Developer Tools
Trust and health
Maintenance
- kedro
- Very active (96%)
- ploomber
- Archived (8%)
Days since push
- kedro
- 1d
- ploomber
- 430d
Archived on GitHub
- kedro
- No
- ploomber
- Yes
Open issues (now)
- kedro
- 163
- ploomber
- 110
Full report
- kedro
- Trust report
- ploomber
- Trust report
Shared compatibility
- Python · kedro: Python runtime · ploomber: Python runtime
Choose kedro if…
- Requirements: Installable via pip or conda, ideal for Python environments..
- Tags unique to kedro: agentic-ai, data-pipelines.
- Also covers Data & Retrieval.
- When your project demands reproducibility and maintainability in pipelines, leveraging Kedro's focus on modular design can greatly enhance these attributes.
When NOT to use kedro
- Avoid using Kedro if your project requirements favor minimal setup and quick experimentation over robust pipeline architecture; its structured framework might feel restrictive.
- If the team is not well-versed in Python or software engineering best practices, Kedro may pose a learning curve that could delay project progress.
Choose ploomber if…
- Requirements: Works with Python versions 3.7 and higher..
- Tags unique to ploomber: data-engineering, data-science, jupyter-notebooks.
- Use Ploomber when you need to iteratively develop and test data pipelines using Python, as it provides native support for such workflows.
When NOT to use ploomber
- Avoid Ploomber if your development process does not involve iterative testing or if direct integration with Jupyter notebooks is unnecessary.
- Do not use Ploomber if you prefer a non-IDE environment and you do not need Python's ecosystem for building data pipelines, as it heavily integrates with IDEs like PyCharm and VSCode.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (kedro-org/kedro) · observed Aug 3, 2026
- GitHub forks (kedro-org/kedro) · observed Aug 3, 2026
- Last push (kedro-org/kedro) · observed Aug 1, 2026
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ploomber/ploomber) · observed Aug 3, 2026
- GitHub forks (ploomber/ploomber) · observed Aug 3, 2026
- Last push (ploomber/ploomber) · observed May 29, 2025
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: kedro 11k · ploomber 3.6k (synced Aug 3, 2026).
Common questions
- What is the difference between kedro and ploomber?
- kedro: Toolbox for production-ready data science. ploomber: The fastest way to build data pipelines. Develop iteratively, deploy anywhere.. See the comparison table for live GitHub stats and shared categories.
- When should I choose kedro over ploomber?
- Choose kedro over ploomber when Requirements: Installable via pip or conda, ideal for Python environments.; Tags unique to kedro: agentic-ai, data-pipelines; Also covers Data & Retrieval; When your project demands reproducibility and maintainability in pipelines, leveraging Kedro's focus on modular design can greatly enhance these attributes.
- When should I choose ploomber over kedro?
- Choose ploomber over kedro when Requirements: Works with Python versions 3.7 and higher.; Tags unique to ploomber: data-engineering, data-science, jupyter-notebooks; Use Ploomber when you need to iteratively develop and test data pipelines using Python, as it provides native support for such workflows.
- When should I avoid kedro?
- Avoid using Kedro if your project requirements favor minimal setup and quick experimentation over robust pipeline architecture; its structured framework might feel restrictive. If the team is not well-versed in Python or software engineering best practices, Kedro may pose a learning curve that could delay project progress.
- When should I avoid ploomber?
- Avoid Ploomber if your development process does not involve iterative testing or if direct integration with Jupyter notebooks is unnecessary. Do not use Ploomber if you prefer a non-IDE environment and you do not need Python's ecosystem for building data pipelines, as it heavily integrates with IDEs like PyCharm and VSCode.
- Is kedro or ploomber more popular on GitHub?
- kedro has more GitHub stars (10,941 vs 3,622). Stars measure visibility, not whether either tool fits your constraints.
- Are kedro and ploomber open source?
- Yes - both are open-source projects on GitHub (kedro: Apache-2.0, ploomber: Apache-2.0).
- Where can I find alternatives to kedro or ploomber?
- GraphCanon lists graph-backed alternatives at kedro alternatives and ploomber alternatives (kedro markdown twin, ploomber 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, kedro or ploomber?
- kedro: Very active. ploomber: Archived. 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 kedro and ploomber?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: kedro trust report; ploomber trust report.