Kedro
Open SourceFundedOpen-source framework for production-ready data and ML pipelines
About Kedro
Kedro is an open-source Python framework designed to help enterprises build, maintain, and scale production-ready data engineering and machine learning pipelines. It applies software engineering best practices to data science workflows, enabling teams to create clean, modular, and reproducible code. Kedro is ideal for organizations seeking to standardize their data pipeline development and improve collaboration across data scientists, engineers, and product teams.
The platform offers a comprehensive set of features including pipeline visualization, a flexible data catalog supporting multiple storage systems and file formats, and seamless integration with popular tools such as Apache Airflow, MLflow, and cloud ML services. Kedro supports test-driven development and coding standards to ensure maintainability and quality. Its deployment flexibility allows for single or distributed machine setups and integration with orchestration tools like Kubeflow and Prefect, facilitating smooth transitions from experimentation to production environments.
Key Capabilities
- ✓Production-ready data and ML pipeline scaffolding
- ✓Pipeline visualization with Kedro-Viz
- ✓Flexible data catalog supporting multiple storage and formats
- ✓Integration with popular ML and orchestration tools
- ✓Support for test-driven development and coding standards
Integrations
Other ML Platforms & MLOps Vendors
View allRelated Buyer Guides
Independent evaluation frameworks for this category.
This profile was compiled by CIOPages from public sources with AI assistance, and may be incomplete or out of date. It is informational only and not an endorsement. Represent this vendor? or .