Looking for a cost-effective way to run your dbt-core projects within Apache Airflow? With Cosmos, you can seamlessly transform dbt-core jobs into Airflow task groups and DAGs with just a few lines of code.
Since its release in early 2023, Cosmos has become the leading solution for integrating dbt-core with Airflow, recently surpassing 1 million downloads.
Why Cosmos?
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Optimize Resources: Use existing Airflow connections—no need for new infrastructure.
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No Licensing Fees: OSS tool with no added costs as you scale.
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Simplify Dependencies: Run dbt in a virtual environment to avoid conflicts with Airflow.
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Automated Testing: Catch issues early with tests triggered after model execution.
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Efficient Scheduling: Use data-aware scheduling to optimize workflows.
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Full Task Control: Turn dbt models into Airflow tasks with retries, alerts, and monitoring.
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See Why People Love Cosmos
Having set up dbt-core on Airflow before, I had to create a lot of internal jobs to achieve what this project does out of the box. With Cosmos and the open source community, it's been great to see best practices in place and how forward-thinking the project is. dbt artifacts automatically spitting out open-lineage datasets to feed into data-aware scheduling? Nice! It's been great and I know it will get better.
Adam Underwood
Senior Data Engineer, Grindr
We conducted a PoC, running dbt with Mage.ai, dbt Cloud, GitHub Actions, and Astronomer Cosmos. In the end, our team voted for Cosmos.
Jensen Yap
Senior Data Engineer, NFTBank.ai
Astronomer Cosmos has allowed us to seamlessly orchestrate our dbt projects using Apache Airflow for our start-up. The ability to render dbt models as individual tasks and run tests after a model has been materialized has been valuable for lineage tracking and verifying data quality. I was impressed with how quickly we could take our existing dbt projects and set up an Airflow DAG using Cosmos.
Justin Bandoro,
Senior Data Engineer, Kevala Inc.
Cosmos has sped up our adoption of Airflow for orchestrating our System1 Business Intelligence dbt Core projects without requiring deep knowledge of Airflow. We found the greatest time-saver in using the Cosmos DbtTaskGroup, which dynamically creates Airflow tasks while maintaining the dbt model lineage and dependencies that we already defined in our dbt projects.
Karen Connelly
Senior Manager, Business Intelligence, System1
With Cosmos, we could focus more on the analytical aspects and less on the operational overhead of coordinating tasks. The ability to achieve end-to-end automation and detailed monitoring within Airflow significantly improved our data pipeline’s reliability, reproducibility, and overall efficiency.
Péter Szécsi
Information Technology Architect, Data Engineer, Hungarian Post
