Kedro
Kedro is a free, open-source Python framework for building production-ready data engineering and data science pipelines.
What Kedro is
Kedro is a free, open-source Python framework for building production-ready data engineering and data science pipelines. Its dataset-driven workflow connects pure Python functions by resolving dependencies automatically. An adaptable project template organizes configuration, source code, tests, documentation, and notebooks. The Data Catalog connects to S3, GCP, Azure, sFTP, DBFS, and local filesystems, and supports tools such as Pandas, Spark, and Dask. Supported formats include CSV, Excel, Parquet, Feather, HDF5, JSON, SQL tables and queries, Spark DataFrames, XML, Delta tables, and Pickle. File-based systems can use data and model snapshots. Kedro-Viz displays lineage, execution time, node status, and dataset statistics. Integrations include Amazon SageMaker, Apache Airflow, Apache Spark, Azure ML, Dask, Databricks, Docker, Jupyter Notebook, Kubeflow, MLflow, and VertexAI. Deployment guidance covers single-machine and distributed targets including Prefect, Kubeflow, AWS Batch, SageMaker, Databricks, and Dask. Kedro runs self-hosted on Linux, installs with pip or conda, and offers VS Code support, documentation, tutorials, and Slack help.
Good
- Free open-source framework
- Dataset-driven dependency resolution
- Broad Data Catalog connections
- Pipeline lineage visualization
- Single-machine and distributed deployment
Watch out
- Self-hosted deployment
- Code-authoring framework
- Project code uses deployment permissions
Who it suits
It is aimed at data scientists, machine-learning engineers, data engineers, and teams building data pipelines. Self-hosted Linux users who prefer Python-based pipeline authoring can install it with pip or conda.
Verdict
Kedro provides a structured Python foundation for data and machine-learning pipelines, with catalog connections, visualization, integrations, and deployment guidance. Teams should assess its self-hosted, code-based model against their environment and pipeline practices.
Plans and prices
From Kedro's own pricing page, checked 2 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Kedro | Free | Open-source Python framework; install with pip or conda |
The facts
Each one read from Kedro's own pages, with the date it was checked.
What it does
- 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.checked 2 Oct 2026
- Deployment
- Kedro documents single-machine and distributed deployment, with targets including Prefect, Kubeflow, AWS Batch, SageMaker, Databricks, and Dask.checked 2 Oct 2026
- IDE support
- The Kedro extension for Visual Studio Code provides enhanced code navigation and autocompletion.checked 2 Oct 2026
- Install
- Kedro can be installed with pip or conda.checked 2 Oct 2026
- Integrations
- Listed integrations include Amazon SageMaker, Apache Airflow, Apache Spark, Azure ML, Dask, Databricks, Docker, Jupyter Notebook, Kubeflow, MLflow, and VertexAI.checked 2 Oct 2026
- Pipeline structure
- Its dataset-driven workflow automatically resolves dependencies between pure Python functions.checked 2 Oct 2026
- Project template
- Kedro provides an adaptable project template for organizing configuration, source code, tests, documentation, and notebooks.checked 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.checked 2 Oct 2026
- Support
- The project points users to its community on Slack for technical questions and provides documentation and tutorials.checked 2 Oct 2026
- Versioning
- The Data Catalog includes data and model snapshots for file-based systems.checked 2 Oct 2026
- Visualization
- Kedro-Viz displays data lineage and pipeline details such as execution time, node status, and dataset statistics.checked 2 Oct 2026
- What it does
- Kedro is an open-source Python framework for building production-ready data engineering and data science pipelines.checked 2 Oct 2026
- Who it is for
- Kedro is aimed at data scientists, machine-learning engineers, data engineers, and teams building data pipelines.checked 2 Oct 2026
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