Apache Airflow
dataops orchestration
Data workflow orchestration platform
Prerequisites:
python
Pros and Cons
Ventajas
- + Industry standard
- + DAGs as Python code
- + Monitoring UI
- + Huge operator ecosystem
- + Active community
- + Industry standard for data orchestration
- + Complete web UI for monitoring
- + Large ecosystem of operators and providers
- + Workflows as code (DAGs in Python)
- + Scalable for thousands of tasks
- + Very active and mature community
Desventajas
- - Can be complex to operate
- - Scheduler single point of failure
- - Demanding initial setup
- - Complex initial setup
- - Resource intensive
- - Steep learning curve
- - Debugging can be difficult
- - Not ideal for real-time tasks
Casos de Uso
- ETL/ELT pipelines
- Data engineering workflows
- Batch processing
- ML pipeline orchestration
- Report automation
- Enterprise data integration
- Batch processing workflows
- Microservices coordination