The text compares building data pipelines with Dagster and Airflow. Dagster takes a different approach by viewing everything as an asset, rather than focusing on DAGs and tasks. This allows for more flexibility and scalability in managing dependencies between assets. Dagster also encourages explicit code writing over templating or Jinja, which is used in Airflow. The documentation and UI experience are also highlighted, with Dagster's supporting Python docstrings making it easier to document assets, while Airflow's UI can be cryptic. Finally, the text discusses how Dagster makes it possible to launch a UI quickly and easily using the `dagster dev` command, which allows for more manageable and scalable graph management compared to Airflow.