Dagster
dataops orchestration
Modern data orchestrator with assets-first approach
Prerequisites:
python
Pros and Cons
Ventajas
- + Modern asset-based approach
- + Integrated type system
- + First-class testing
- + Excellent UI
- + Easy local development
- + Focus on data assets (Software-Defined Assets)
- + Excellent observability and data lineage
- + Integrated and easy testing
- + Modern UI with asset visualization
- + Strong typing and validation
- + Native dbt integration
Desventajas
- - Less mature than Airflow
- - Smaller community
- - Migration from Airflow requires effort
- - New concepts to learn (assets, ops, jobs)
- - Smaller community than Airflow
- - Fewer integrations than Airflow
- - Can be overkill for simple pipelines
- - Dagster Cloud has costs
Casos de Uso
- Modern data orchestration
- Asset lineage tracking
- Data quality pipelines
- Analytics engineering
- Asset-based data pipelines
- Data mesh and data products
- dbt integration
- ML pipeline orchestration
- Data quality and observability
- Modern data platforms