10 Common Misconceptions about Airflow

With more than 10 million downloads per month, Airflow is ubiquitous in data orchestration across nearly every industry. Originally created in 2015, the project has evolved alongside the needs of data teams everywhere as they’ve dealt with growth of the major clouds and cloud-native data warehouses, and most recently, the rise of the modern data stack. (Fun fact: Airflow has been around longer than AirPods).

Through all the changes data teams have faced, Airflow has picked up release velocity and stability along the way, to the point where Airflow releases now happen like clockwork:

This is undoubtedly a big part of why Airflow continues to grow in popularity, but on the flip side, a long tenure inevitably means some users get stuck along the way. Whether somebody tried Airflow once a few years ago as a personal project, or works in an environment where upgrades to key tools are difficult or infrequent, some impressions from versions long past are no longer relevant in versions available today.

With this post, we want to reset some of those old Airflow impressions. We’ll detail common misconceptions about Airflow and explain why they may have been true at one time, but aren’t in the Airflow of 2023.

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