[{"data":1,"prerenderedAt":12},["ShallowReactive",2],{"stack-tr-en-apache-airflow":3},{"tagline":4,"description":5,"strengths":6,"useCase":11},"The data workflow orchestrator that became the industry standard.","Airflow describes pipelines in Python DAGs: tasks, dependencies, retries, scheduling. Its flexibility, provider ecosystem and clear UI make it the reference for orchestrating batch ETL, ML pipelines and analytical processing.",[7,8,9,10],"DAGs in pure Python: readability, testability, versioning.","Native providers: AWS, GCP, Azure, Snowflake, dbt, Spark.","Cron-like scheduling, retries, SLA, alerting.","Astronomer, MWAA, Cloud Composer: managed across three clouds.","ETL orchestration, ML pipelines, analytical batch jobs.",1792675976901]