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Kedro
What Kedro is
Kedro is a free, open-source Python framework for building data engineering and data science pipelines. Its dataset-driven workflow resolves dependencies between pure Python functions, while an adaptable project template organizes configuration, code, tests, documentation and notebooks. The Data Catalog connects to S3, GCP, Azure, sFTP, DBFS and local filesystems, and works with tools including Pandas, Spark and Dask. Supported data formats include CSV, Excel, Parquet, Feather, HDF5, JSON, SQL tables and queries, Spark DataFrames, XML, Delta tables and Pickle. For file-based systems, the catalog can keep data and model snapshots. Kedro-Viz displays pipeline lineage, execution time, node status and dataset statistics. Integrations include Amazon SageMaker, Apache Airflow, Databricks, Kubeflow and MLflow. Deployment guidance covers single-machine and distributed setups. Kedro runs as normal Python code with the permissions of its deployment environment, and can be installed with pip or conda. It runs on Linux in a self-hosted environment.
Who it suits
Kedro is aimed at data scientists, machine-learning engineers, data engineers and teams building data pipelines. It suits people who want to author pipelines in Python and organize them in a structured project.
What it does well
- Free and open source.
- Catalog connects to cloud and local storage.
- Kedro-Viz shows lineage and pipeline details.
- Supports file-based data and model snapshots.
- Deployment guidance covers single-machine and distributed setups.
What to know first
- Transformation interface is code-based.
- Project code runs with its environment’s permissions.
- Linux and self-hosted are the listed platforms.
Plans
| Plan | Billed and limits | Price |
|---|---|---|
| Kedro | Open-source Python framework; install with pip or conda | Free |
As kedro.org lists them, read 2 Oct 2026. The maker's own page has the final word.
Verdict
Kedro offers a structured Python workflow with a broad Data Catalog and pipeline visualization. Teams should be comfortable authoring code and managing deployment in their own environment.
Facts from Kedro's own pages
- Data catalog
- The Data Catalog connects to S3, GCP, Azure, sFTP, DBFS, and local filesystems, and supports formats and tools including Pandas, Spark, and Dask. · kedro.org, 2 Oct 2026
- Deployment
- Kedro documents single-machine and distributed deployment, with targets including Prefect, Kubeflow, AWS Batch, SageMaker, Databricks, and Dask. · kedro.org, 2 Oct 2026
- IDE support
- The Kedro extension for Visual Studio Code provides enhanced code navigation and autocompletion. · kedro.org, 2 Oct 2026
- Install
- Kedro can be installed with pip or conda. · kedro.org, 2 Oct 2026
- Integrations
- Listed integrations include Amazon SageMaker, Apache Airflow, Apache Spark, Azure ML, Dask, Databricks, Docker, Jupyter Notebook, Kubeflow, MLflow, and VertexAI. · kedro.org, 2 Oct 2026
- Pipeline structure
- Its dataset-driven workflow automatically resolves dependencies between pure Python functions. · kedro.org, 2 Oct 2026
- Project template
- Kedro provides an adaptable project template for organizing configuration, source code, tests, documentation, and notebooks. · kedro.org, 2 Oct 2026
- Security model
- Kedro describes itself as a code authoring framework and says project code runs as normal Python with the permissions of its deployment environment. · docs.kedro.org, 2 Oct 2026
- Support
- The project points users to its community on Slack for technical questions and provides documentation and tutorials. · github.com, 2 Oct 2026
- Versioning
- The Data Catalog includes data and model snapshots for file-based systems. · kedro.org, 2 Oct 2026
- Visualization
- Kedro-Viz displays data lineage and pipeline details such as execution time, node status, and dataset statistics. · kedro.org, 2 Oct 2026
- What it does
- Kedro is an open-source Python framework for building production-ready data engineering and data science pipelines. · kedro.org, 2 Oct 2026
- Who it is for
- Kedro is aimed at data scientists, machine-learning engineers, data engineers, and teams building data pipelines. · kedro.org, 2 Oct 2026
Where Kedro stands on Freedom251
- Data Transformation Tools#23 of 37
- Data Version Control Tools#25 of 36