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Launched on March 14th, 2018
Our Enterprise Apache Airflow includes one-click DAG deployment through our Astro CLI, a full monitoring stack, access to our library of hooks and operators, and professional support. The entire package is Kubernetes-deployable; it can be hosted entirely on your infrastructure.
Fantastic and very knowledgable team that goes to great lengths identifying customers' needs and making sure to support them. The solution is extremely flexible, hence the need to dig a bit deeper what specific use cases to tackle with Astronomer.
The new UI is the slickest UI in an analytics product ever!
Astronomer's greatest value-add is the not having to deal with the devops side of setting up Airflow; which is absolutely a non-trivial task, given the capabilities of using Celery to dynamically spin up/down workers as separate, distinct servers.
This abstraction (and the excellent support we received from Astronomer's team) allowed our Data Science team to replicate the ETL capabilities of tools we were already subscribed to within a few weeks. And with pricing centered around workers, we were able to cut costs when switching over from a per-row pricing model. And since we're now on Airflow instead of a button-click tool, we now have all kinds of flexibility with our data that we didn't have before.
Awesome framework, packaged by an excellent team who truly understands their niche.
Definitely would recommend this to anyone looking for a more roll-your-own ETL setup or just a nice, hosted workflow scheduler.
Curios to understand what AirFlow is? Is it to build custom data-munging pipelines?
