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Airflow is a platform to programmatically author, schedule and monitor workflows.
ETL Software Free
• Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation • Easily define your own operators, executors and extend the library so that it fits the level of abstraction. • Airflow pipelines are lean and explicit. •Parameterizing your scripts is built into the core of Airflow using the powerful Jinja templating engine. •Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers.
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
• Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation • Easily define your own operators, executors and extend the library so that it fits the level of abstraction. • Airflow pipelines are lean and explicit.
What are the benefits?
• Dynamic • Extensible • Elegant • Scalable
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Apache Airflow is an open-source tool that works by programmatically authoring, scheduling and monitoring workflows.
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Apache Airflow is an open-source tool for authoring, scheduling and monitoring workflows. In other words, it performs computational workflows that are complex and also data processing pipelines.
Airflow is ideal for your business if you are involved in executing very long scripts are even keeping a calendar of big data processing batch jobs. Apache airflow has an airflow scheduler that executes your tasks on an array of workers while following the specified dependencies. It has a rich command line utility that makes performing complex surgeries on DAGs (Directed Acyclic Graph- a collection of all the tasks you want to run, organized in a way that reflects their relationships and dependencies) very easy.
It also has a rich user interface that makes it easy to visualize pipelines running in production, monitor progress and, and troubleshoot issues when needed.Airflow workflows are expected to look similar from a run to the next, this allows for clarity around unit of work and continuity.Airflow provides a simple query interface to write SQL and get results quickly, and a charting application letting you visualize data.
The Airflow scheduler monitors all tasks and all DAGs, and triggers the task instances whose dependencies have been met. Behind the scenes, it monitors and stays in sync with a folder for all DAG objects it may contain, and periodically (every minute or so) inspects active tasks to see whether they can be triggered.
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It offers robust functionality through a command line interface (CLI).
Medium (50 to 1000)
Easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment.
Apache Airflow is a WMS that defines tasks and their dependencies as code, executes those tasks on a regular schedule, and distributes task execution across worker processes. Airflow offers an excellent UI that displays the states of currently active and past tasks, shows diagnostic information about task execution.