--- title: "kedro vs ploomber" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kedro-org-kedro-vs-ploomber-ploomber" tools: ["kedro-org-kedro", "ploomber-ploomber"] --- # kedro vs ploomber *GraphCanon updated Aug 3, 2026* ## 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. [kedro](https://kedro.org) reports 11k GitHub stars, 1.1k forks, and 163 open issues, last pushed Aug 1, 2026. [ploomber](https://docs.ploomber.io) has 3.6k stars, 243 forks, and 110 open issues, last pushed May 29, 2025. Figures are from public GitHub metadata via [kedro's repository](https://github.com/kedro-org/kedro) and [ploomber's repository](https://github.com/ploomber/ploomber). | | [kedro](/tools/kedro-org-kedro.md) | [ploomber](/tools/ploomber-ploomber.md) | | --- | --- | --- | | Tagline | Toolbox for production-ready data science | The fastest way to build data pipelines. Develop iteratively, deploy anywhere. | | Stars | 10,941 | 3,622 | | Forks | 1,066 | 243 | | Open issues | 163 | 110 | | Language | Python | Python | | Adopt for | Kedro is ideal for productionizing data science projects through its emphasis on software engineering discipline within the Python environment. | 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 | - | - | | Runtime | - | - | | License | Apache-2.0 | 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. | | Categories | Data & Retrieval, Developer Tools | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [kedro](/tools/kedro-org-kedro.md) | [ploomber](/tools/ploomber-ploomber.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 1d | 430d | | Archived on GitHub | No | Yes | | Open issues (now) | 163 | 110 | | Full report | [trust report](/tools/kedro-org-kedro/trust.md) | [trust report](/tools/ploomber-ploomber/trust.md) | ## Shared compatibility - **Python**: [kedro](/tools/kedro-org-kedro.md) - Python runtime; [ploomber](/tools/ploomber-ploomber.md) - Python runtime ## Decision facts: kedro - **Requirements:** Installable via pip or conda, ideal for Python environments. - **Adopt for:** Kedro is ideal for productionizing data science projects through its emphasis on software engineering discipline within the Python environment. ## Decision facts: ploomber - **Requirements:** Works with Python versions 3.7 and higher. - **Adopt for:** 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. - **License detail:** 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. ## Choose when ### 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. ### 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 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 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. ## 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](/tools/kedro-org-kedro/alternatives) and [ploomber alternatives](/tools/ploomber-ploomber/alternatives) ([kedro markdown twin](/tools/kedro-org-kedro/alternatives.md), [ploomber markdown twin](/tools/ploomber-ploomber/alternatives.md)), 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](/compare/kedro-org-kedro-vs-ploomber-ploomber.md) 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](/tools/kedro-org-kedro/trust); [ploomber trust report](/tools/ploomber-ploomber/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kedro-org-kedro`](/api/graphcanon/graph?tool=kedro-org-kedro) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_