Apache Airflow vs. Axway Managed File Transfer

For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.

Incentivized

I do not see where you would use this in any other scenarios. It's a purpose built system for sending and receiving data.

Incentivized

• Apache Airflow is one of the best Orchestration platforms and a go-to scheduler for teams building a data platform or pipelines.
• Apache Airflow supports multiple operators, such as the Databricks, Spark, and Python operators. All of these provide us with functionality to implement any business logic.
• Apache Airflow is highly scalable, and we can run a large number of DAGs with ease. It provided HA and replication for workers. Maintaining airflow deployments is very easy, even for smaller teams, and we also get lots of metrics for observability.

Incentivized

• If you use Axway SecureTransport with their edge server. The system separates your user accounts from the first point of entry into the system. This is done by creating an edge device in your DMZ that acts only as a proxy to the backend ST server.
• Their support has been really good when you have a questions or issues with the version you are on. They respond pretty quickly to your open cases.
• I also like the fact that their system can be really customizable. This does take a little bit of knowledge of how the system works. I did go to a 4 day class that Axway provided back in version 4.
• They support a wide range of security and automation when it comes to sending/receiving files.
• They have low CVE vulnerabilities and they keep up with the latest security holes that may arise.
• SecureTransport is a pretty solid platform and it's pretty hands off once it's up and running. We did have to tweak a few things regarding the memory allocated to the running services and there are a still few open bugs that are supposed to be released in the next SecureTransport. Those are not causing any issue on our side.
• You can create different templates for your HTTPS sites. This is useful if you have different needs for your customers.

Incentivized

• A local "dry run" or IDE plugin that can validate and simulate DAG execution without needing a full environment.
• Better feedback on DAG parse errors in the UI or CLI.
• Navigating large DAGs with hundreds of tasks can be slow and hard to understand visually.

Incentivized

• I have come a cross several bugs that came up in their new releases, but this is kind of expected given they support a wide range of technologies in terms of B2B transfers or ad-hoc transfers.
• Support is sometimes difficult to communicate with just because of them being out of India. They are responsive and know their stuff when it comes to SecureTransport.

Incentivized

For its capability to connect with multicloud environments. Access Control management is something that we don't get in all the schedulers and orchestrators. But although it provides so many flexibility and options to due to python , some level of knowledge of python is needed to be able to build workflows.

Incentivized

Apache Airflow is suited for a much wider set of use cases compared to Databricks. You can run it anywhere, and there is also no vendor lock-in. With Airflow, we can utilize almost any compute engine. Same thing we want to do with Databricks. There might be some level of difficulty based on the support.

Incentivized

I have not used another product other than SecureTransport. I have only researched to see if there are any alternatives better. Frankly we just don't have the time to invest in switching either. SecureTransport does what it needs to do in our environment.

Incentivized

• Most of the ETL processes were automated, cutting down on human labor.
• Apache Airflow's user interface (UI) was very informative and straightforward.
• Since ETL processes were providing data via airflow, we were able to gain a deeper comprehension of the data at hand.

Incentivized

• Once the system is set up and operational, the only internal support would be to configure new accounts or research failed transmissions. It's really hands off once you have it up and running. It doesn't require a bunch of support or baby sitting.
• We are able to offer new services to our business customers which benefits both sides.

Incentivized