Kedro

Data and development workflow framework for productionizing ML models.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is Kedro?

Kedro is a data and development workflow framework that implements best practices for building, testing, and deploying machine learning pipelines. It streamlines the process of creating reproducible and maintainable data science projects.

Key differentiator

Kedro stands out by providing a robust framework that emphasizes reproducibility and maintainability, making it ideal for teams focused on productionizing machine learning models.

Capability profile

Strength Radar

Reproducible pip…Support for vers…Integration with…Extensive docume…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Reproducible pipelines with a modular structure

Support for version control and testing of data pipelines

Integration with various data storage solutions

Extensive documentation and community support

Fit analysis

Who is it for?

✓ Best for

Teams that need to build, test, and deploy ML pipelines with best practices

Projects requiring reproducibility and maintainability in data science workflows

✕ Not a fit for

Developers looking for a cloud-based managed service for ML pipeline deployment

Small projects or prototypes where lightweight solutions are preferred over structured frameworks

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with Kedro

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →