#java #airflow #azkaban #cloud_native #data_pipelines #job_scheduler #orchestration #powerful_data_pipelines #task_scheduler #workflow #workflow_orchestration #workflow_schedule

Apache DolphinScheduler is a powerful tool for managing data workflows. It makes it easy to create and manage complex tasks with a user-friendly interface and low-code options. You can deploy it in several ways, including standalone, cluster, Docker, and Kubernetes, making it flexible for different environments. It's highly reliable, scalable, and performs much faster than other platforms, supporting millions of tasks daily. The tool also offers features like versioning, state control of workflows, multi-tenancy support, and permission control. This helps you manage your data pipelines efficiently and reliably, saving time and effort.

https://github.com/apache/dolphinscheduler

#python #airflow #apache #apache_airflow #automation #dag #data_engineering #data_integration #data_orchestrator #data_pipelines #data_science #elt #etl #machine_learning #mlops #orchestration #python #scheduler #workflow #workflow_engine #workflow_orchestration

Apache Airflow is a tool that helps you manage and automate workflows. You can write your workflows as code, making them easier to maintain, version, test, and collaborate on. Airflow lets you schedule tasks and monitor their progress through a user-friendly interface. It supports dynamic pipeline generation, is highly extensible, and scalable, allowing you to define your own operators and executors.

Using Airflow benefits you by making your workflows more organized, efficient, and reliable. It simplifies the process of managing complex tasks and provides clear visualizations of your workflow's performance, helping you identify and troubleshoot issues quickly. This makes it easier to manage data processing and other automated tasks effectively.

https://github.com/apache/airflow