Astro by Astronomer Reviews & Product Details - Page 4

I like that it is flexible, well documented, has good support. Its UI is pleasing too. It's fast, allows to schedule lots differents jobs by nature (data engineering, ML models, MLOps, etc). It's overall a fantastic orchestration service. Review collected by and hosted on G2.com.

I wish it was easier to see duration of each task over the recent runs.

I also wish we didn't have to have all our ETLs in one github repository as it makes going from dev to prod messy at times.

I would love to see even more training for new people. As an experienced user it clearly has a high learning curve and find myself having to explain stuff a lot to people!

Quite a lot of breaking changes with google dependencies especially - can be quite time consuming to just maintain the instances running despite no changes to code. Review collected by and hosted on G2.com.

I like the fact that they have come a long way from being a startup supporting opensource airflow to becoming an enterprise focusing on what their customers want. They have a history of feature rich development to provide best cutomer support. Their dev and production enviornment deployment via CI/CD provide an ease of implementation and integration of Airflow for their customers. I find the system easy to use that gives me confidence. They had their ups and downs as an orgination but they have come a long way from there. I am happy to say Fanduel 's decion to use Astronomer has proven to be a good success. Review collected by and hosted on G2.com.

There are no major problems in using Astro but some quirks here and there. Overall I like the way they are building the product and support Airflow. Review collected by and hosted on G2.com.

The Astro by Astronomer is a well-engineered product with the flexibility to use

The talent at Astronomer makes the process as smooth as possible

The team is supportive and very knowledgeable Review collected by and hosted on G2.com.

The experience of using astronomer for the migration of existing DAGs and new developments has been great, and all positive. Review collected by and hosted on G2.com.

I've worked with Airflow for the last 6 year, both administering it myself and using managed services like AWS MWAA. In my opinion Astronomer is the only feasible managed service currently available for Airflow. It's the first managed service I've used that does not entail a surprising number of performance bugs even when used only as an orchestration engine (which generally deferable functionality has resolved), and the only approach I would recommend if you want to also use it as an execution engine in its own right. In our use case, our per deployment costs were cut in half relative to AWS MWAA. Additionally it greatly increases ease of use, so non-engineering teams can make use of it with minimal need for engineering staff once it's set up.

Additionally, customer service is excellent. Always a response time proportional to the level of severity, and even complex bug fixes (generally caused by underlying Airflow libraries, not Astronomer itself) that have popped up had tested fixes available within a few days. If you're using Airflow for a non-trivial, production workload and not managing the cluster yourself, I don't think there's any other way to go than Astronomer. Review collected by and hosted on G2.com.

Typical painpoints of using a managed service and the limited access that entails, particularly around the shared-compute cluster options and lack of CLI access to remote deployments. That they're serious about addressing with developing new features to ease these painpoints shows they take issues of access more seriously than most managed service providers (Airflow-based and beyond). Review collected by and hosted on G2.com.

When working at a startup with limited resources, we don't have time to worry about self-managing Airflow. Astronomer enabled us to get started with Airflow very quickly without the hassel of setting it up ourselves or worrying about as much maintenance. The customer support is amazing. The field engineer assigned to us is very smart and proactive to make sure all of our requirements are met. Review collected by and hosted on G2.com.

Nothing to dislike. I've worked at companies where we self-hosted Airflow which was such a hassel. Astronomer makes everything so much easier. Review collected by and hosted on G2.com.

Easy to implement and maintain. Setup is pretty quick and the painful parts of managing Airflow are removed. Deploying and upgrading are simple. Also very easy to get a local environment up and running, which is a big win. The Docker based deployments make it easy to test out version upgrading locally before deploying. Astro CLI is great for implementing a CI/CD process.

Customer service team has been great to work with - very responsive and quick to escalate to more technical team members as needed.

Overall a great option for easy Airflow deployment - I can mostly forget about the infrastrcuture and just focus on pipeline development. Review collected by and hosted on G2.com.

Astronomer has rolled out a few new features and/or products over the past year or so that have looked great in the marketing material and demos, but have been less impressive under the hood. Cloud IDE being the latest. Great potential, just still a bit half baked and not worth encorporating on my current project (yet). Great to see Astro consistently working towards value adding features though.

Relatively high price - probably wouldn't be worth it for smaller use cases or companies. Review collected by and hosted on G2.com.

I can solely focus on my development without worrying about infra side issues. Before moving to Astronomer, most of my time spent searching about 'Task not getting queued', 'Zombie processes' 'Scheduler not running'... nad never got enough time for development. Astronomer made it super easy for me. That's why this is the third project I'm doing where I've recommended Astronomer to the client as a freelancer in their team. Review collected by and hosted on G2.com.

I never got anything bad up until now. Just also wanted have access to Airflow side CLI to execute certain commands which I sometimes need for stuff like bulk backfilling etc. And very recently had an issue with getting in touch with support with one of my query. Review collected by and hosted on G2.com.

Of the three best known managed Airflow options (MWAA, Cloud Composer, Astronomer), I think Astronomer is the most streamlined and easy-to-use. The Docker image/runtime is well thought out, and the hybrid managed Dataplane option has sensible ways of doing things and removes the burden of maintaining the deployment. I love the Astro CLI and how easy it is to customize the base Airflow image they provide. The docs are good and they are closest to the actual core Airflow community. Review collected by and hosted on G2.com.

Pricier than the other two, but IMO the extra features are well worth it. Charging by task run also requires care. Outside of pricing/cost though... it's great. I gave them a 9 instead of a 10 because of the cost. Review collected by and hosted on G2.com.

Astronomer has transformed my data pipeline journey as a software engineer. Its intuitive interface and drag-and-drop functionality make designing and troubleshooting Airflow DAGs a breeze. Real-time visualization offers quick insights into DAG runs, enhancing monitoring. Collaborative features and scalability seal the deal, making it a must-have tool for managing projects of any size. Review collected by and hosted on G2.com.

While Astronomer is a game-changer, there's room for growth. New users might face a slight learning curve despite the user-friendly interface. Expanding the range of pre-built operators would add flexibility. Although the documentation is decent, more detailed guides, especially for advanced features, would be a welcome addition. Overall, refinement in these areas would enhance the experience even more. Review collected by and hosted on G2.com.

The fact that it is a SaaS lets our team focus on the coding side; it is quite simple to start using Airflow as you can skip all the initial setups. This is particularly useful for those teams that started using Python and are more distant from the infra side (i.e. data Scientists, analysts, etc.). Review collected by and hosted on G2.com.

I feel that the monitoring dashboard is not rich enough in all circumstances so that we can fully understand possible issues there. For instance, there is no option for accessing KubernetesPod settings alongside our cloud account. Review collected by and hosted on G2.com.