Overall Satisfaction with Matillion
Matillion is being used by Data Engineering, which is a part of the Purple Analytics department. No other departments are using it. Matillion helps us automate our data pipelines. It gives us a platform on which we can schedule Python scripts, and provides an easy workspace where we can design and implement our workflows. The Matillion server is easy to maintain, which was a problem before we switched from our previous platform. Matillion makes it easy to perform ETL operations on our data, whether it starts in our data warehouse or not. It gives us plenty of flexibility in how we design our jobs. And it's super easy to use.
- The workspace is drag and drop, which makes it intuitive and easy to use.
- Server creation and management is robust. We haven't had to worry too much about it once we got it created.
- The job scheduler is very simple and intuitive.
- Matillion allows you to run Python, which grants almost unlimited flexibility, even without using any other components.
- The Python script component needs a friendlier window in which to edit your scripts. The script is not searchable, and tabbing is frustrating.
- The High Availability server configuration was not working for us. It was allowing duplicate jobs to run, and causing a lot of confusion in the scheduler. Love the idea, but the implementation fell short.
- Better alerting around queued jobs would be nice. Sometimes jobs start queuing and nothing runs. Usually this is the result of a badly written job, but it would be nice to get alerts.
- Matillion is an essential part of our stack, which has transformed how we use data to make business decisions. The value is immense, though hard to quantify in a review.
We tested Matillion for about two weeks. By the time we were done testing, we were writing transformations. At that point, we were extremely comfortable with the tool, and we successfully migrated all of our existing code over to Matillion in a few weeks. The learning curve for Matillion is shallow.
Our entry level Data Engineers don't need any hand holding with this tool. A very quick demonstration is generally all that is required. After that, the tool is intuitive enough that even a beginner can use it.
Our entry level Data Engineers don't need any hand holding with this tool. A very quick demonstration is generally all that is required. After that, the tool is intuitive enough that even a beginner can use it.
We used Airflow for a year before switching to Matillion. We switched to Matillion because the Airflow servers were not stable, and we didn't have any in-house expertise that could manage the Linux OS which Airflow is built on. We were constantly frustrated by the fact that we had to wait for a consultant whenever we wanted to manage one of the servers, or if something was down we had to wait for someone to fix it. Also, Airflow doesn't have a GUI that is drag and drop. It is a lot more work to manage the flow of the scripts in Airflow, and requires a lot more explanation, especially for an entry level data engineer. There is a lot more coding in Airflow, which is fine if you are a good coder. However, Matillion offers a bigger tool set for those who just want to focus on building an ETL pipeline, and don't care to do a lot of coding.