Automate Airflow activities with advanced scheduling functionality
Integrate Airflow DAGs into business workflows
Enable Developers to focus on higher value work instead of scheduling tasks
Leverage more advanced scheduling functionality
Airflow is popular among developers that need to manage and monitor data pipelines. Users develop Python language scripts that define Directed Acyclic Graphs (DAGs). These DAGs specify dependencies and a sequence of steps (or tasks) to run either on a defined schedule or based on external event triggers.
Our adapter for Airflow provides seamless integration and automation of Airflow DAG executions in your Tidal-managed processes. With more robust scheduling functionality than the basic features in Airflow, Tidal enables you to include complex DAGs as Airflow jobs within your enterprise workflows and schedule those jobs based on other dependencies and resources. Centralized management frees up developers from monitoring and scheduling tasks so they can focus on higher value activities.
This adapter offers compatibility with Airflow v1 and v2 as well as Airflow activities embedded in Google Cloud Composer. With our integration, you can:
Tidal can orchestrate Airflow workflows whether they're running on-prem or in the cloud.
Tidal can simplify and optimize the scheduling of Airflow jobs and add advanced workflow management capabilities. Learn about the value of the adapter and how to integrate Airflow DAGs into enterprise processes in this short video.
OUR CORE PLATFORM
A unified platform for centralized management and control of job scheduling across business, operations and IT processes. Tidal Automation Platform >