AI / ML ML Pipeline stable
Kedro
Framework for production-quality, reproducible data science code
10.0K stars
250 contributors
Since 2019
ML development framework creating reproducible, maintainable pipelines with data catalog, standardized project structure, and visualization tools.
License
Apache-2.0
Min RAM
512 MB
Min CPUs
1 core
Scaling
single_node
Complexity
intermediate
Performance
medium
Self-hostable
✓
K8s native
✕
Offline
✕
Pricing
fully free
Docs quality
excellent
Vendor lock-in
none
Use cases
- ✓ Standardize ML project structure across teams
- ✓ Build reproducible data transformation pipelines
- ✓ Visualize data dependencies with Kedro-Viz
- ✓ Transition from notebooks to production code
Anti-patterns / when NOT to use
- ✕ Opinionated project structure may not fit all teams
- ✕ Learning curve for catalog system
- ✕ Less suited for real-time or streaming
- ✕ Smaller community than Airflow/MLflow
Integrates with
Complements
Compare with alternatives
Replaces / alternatives to
Technical specs
Language
Python
API type
SDK
Protocols
HTTP
Deployment
pip
SDKs
python
Community
GitHub stars 10.0K
Contributors 250
Commit frequency weekly
Plugin ecosystem none
Backing McKinsey QuantumBlack
Funding corporate
Release
Latest version
— Last release —
Since 2019
Best fit
Team size
solosmallmedium
Industries
generalconsultingfintechresearch