- It enabled an enterprise data-warehouse to be set up and operated, quickly and cheaply.
- The pipeline UI provides a means to present solutions to analysts and non-tech management for review and agreement.
Compared to the likes of traditional ETLs, like Informatica, SnapLogic, and Talend, or even raw Python scripts, this product needs no improvement, as it is so much better.
There have been some issues with stability over the first year, but Matillion support is very responsive. I have allowed them to log into our system on occasion.
There are no issues with scalability if one strictly does all transformations in-database, using Redshift’s DDL/SQL.
All the ‘heavy-lifting’ is done by Redshift, as it is MPP. Simply adding more nodes deals with scalability. It is worth noting that Matillion does not cost more if you add more Redshift nodes.
If one uses Python components (as opposed to UDFs), one may encounter scalability issues.
The CPU utilization in WatchTower, of Matillion’s single EC2 (it is not, itself, MPP), will peak. Therefore, it is best to keep a close watch over what your data engineers are doing with Python components.
I would give technical support a rating of 5/5.
We used Informatica, SnapLogic, and Talend. They do not work well with Redshift and they cost more. They do not understand MPP and much of what they do is outside of Redshift, i.e., not in-database.
You need to put them on a bigger EC2 or buy multiple licenses and have multiple EC2s to manage, in order to get scalability.
The initial setup was very straightforward, as it’s all done from the AWS Marketplace. A wizard steps you through the process of setup. Due to Matillion’s clean and clear architecture, there is not much to configure before one is up and running.
Regardless of the quantity of your data, the size of your cluster, or variety of source systems, the price of Matillion is the same.
The only variable that changes what you pay Matillion is the size of your data engineering team.
As soon as you can, lock in the yearly discounted price with Matillion, as your level of support availability will increase.
We evaluated Informatica, SnapLogic, Talend, Sqoop, and pure Python scripts. Don’t go with any of these if your data can be categorized as any two of the following: volume, variety, and velocity.
Remember, what Matillion does is simply orchestrate the required jobs. It stands back and lets Redshift do what it is good at.