Airflow vs Apache Beam: What are the differences?
Airflow: A platform to programmaticaly author, schedule and monitor data pipelines, by Airbnb. Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed; Apache Beam: A unified programming model. It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
Airflow and Apache Beam can be primarily classified as "Workflow Manager" tools.
Airflow is an open source tool with 13.3K GitHub stars and 4.91K GitHub forks. Here's a link to Airflow's open source repository on GitHub.
According to the StackShare community, Airflow has a broader approval, being mentioned in 98 company stacks & 162 developers stacks; compared to Apache Beam, which is listed in 9 company stacks and 4 developer stacks.