![]() ![]() Source: Apache Airflow What is Apache Airflow used for?Īirflow works with batch pipelines which are sequences of finite jobs, with clear start and end, launched at certain intervals or by triggers. Other tech professionals working with the tool are solution architects, software developers, DevOps specialists, and data scientists.Ģ022 Airflow user overview. No wonder, they represent over 54 percent of Apache Airflow active users. The platform was created by a data engineer - namely, Maxime Beauchemin - for data engineers. The tool represents processes in the form of directed acyclic graphs that visualize casual relationships between tasks and the order of their execution.Īn example of the workflow in the form of a directed acyclic graph or DAG. What is Apache Airflow?Īpache Airflow is an open-source Python-based workflow orchestrator that enables you to design, schedule, and monitor data pipelines. This article covers Airflow’s pros and gives a clue why, despite all its virtues, it’s not a silver bullet.īefore we start, all those who are new to data engineering can watch our video explaining its general concepts. It still remains a leading workflow management tool adopted by thousands of companies, from tech giants to startups. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. But, apparently, things were even more difficult before Apache Airflow appeared. The heavy lift that is data engineering exists in sharp contrast with something as easy as breathing or as fast as the wind. How to get started with Apache Airflow? Reading time: 11 minutes.The complexity of the production setup and maintenance. ![]() Open-source approach: an active and continuously growing community.Full REST API: easy access for third parties.A large number of hooks: extensibility and simple integrations.Task concurrency and multiple schedulers: horizontal scalability and high performance.Everything as code: flexibility and total control of the logic.Use of Python: a large pool of tech talent and increased productivity.
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