Ease of Use and Reusability for Excellent ROI
Updated November 30, 2020

Ease of Use and Reusability for Excellent ROI

Matthew Burr | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Matillion

We use Matillion to bring together data from multiple sources - our application, Salesforce, Qualtrics, etc. - into a central data warehouse for use throughout the business in reporting, both internally and externally. Matillion performs the ETL that transforms this raw data into a structure in Redshift useful for reporting.
  • It integrates well with Amazon Web Services, like S3 and Redshift
  • It makes good use of Redshift to perform ETL quickly
  • The ability to parameterize ETL jobs with variables makes it possible to get a lot of reuse from ETL jobs
  • Integration with source control is a challenge; we had to roll our own solution to pull our Matillion jobs via its API into files we could add to source control
  • It can be a challenge to avoid conflicts when multiple people are developing jobs in the same project
  • It's only available on Redhat flavors of Linux (e.g. Amazon Linux, Redhat, CentOS)
  • Matillion has dramatically decreased the time it takes to create new ETL
  • Matillion has reduced the amount of time it takes to execute our daily ETL processing (by 50% or more)
  • Matillion has increased the number of people who can develop ETL by making ETL development easier
  • Matillion has increased the variety of data sources we can bring into our data warehouse
  • Matillion has made it a little harder to manage source control and deployment
It's very easy to use because of its graphical nature. Ultimately, it is a wrapper for activities you could do using SQL, Python, and AWS services, and by presenting those activities in a simple interface it makes it easier to perform them without having to worry about a lot of extraneous details.
We were able to get up and running with Matillion within a month. With no real training in the tool, we were able to develop useful jobs and an entire job framework on Matillion within that month. As we got more familiar with it, within three months, we were able to take advantage of additional features to create a framework where bringing new data in from our application is as simple as adding an entry to a table.
We don't have a particularly large volume of data (less than 200GB), but as we've added more and more data, we are able to fully reprocess our data in about 2.5 hours (vs. over 6 hours it used to take to incrementally process our data in our old ETL system). We're not even using the Enterprise version of the product; if we did, we would get even greater scale.
SQL Server Integration Services (SSIS) is built around the Microsoft ecosystem; we needed something that was either "ecosystem-agnostic" or focused on AWS, which Matillion is. SSIS has very limited ability to parameterize jobs/packages compared to Matillion, reducing the reusability of jobs/packages.

Pentaho was too difficult to set up, and was also relatively limited in its parameterization, so that jobs weren't as reusable.

Ultimately, we select Matillion for its ease of use, its ability to create reusable jobs, its fit for our ecosystem, and its cost.
Amazon Redshift, PostgreSQL, Amazon Elastic Compute Cloud (EC2)
Matillion is really well suited to environments using Redshift or Snowflake, and that rely on Amazon Web Services. It is also well suited to scenarios where you need to perform a lot of similar ETL tasks with small variations that could be parameterized. It's great if you want to get up-and-running quickly, and don't want to spend a ton of time in configuration and setup; you can get going very quickly out-of-the-box. It would be less appropriate in on-premise scenarios, where all of your data is stored on-premise. If you don't use AWS, you won't get as much value out of it. Also, in environments with large teams and lots of developers modifying jobs simultaneously, it can be a challenge to coordinate work and manage changes.

Matillion Feature Ratings

Connect to traditional data sources
Connecto to Big Data and NoSQL
Simple transformations
Complex transformations
Metadata management
Business rules and workflow
Testing and debugging
Integration with data quality tools
Not Rated
Integration with MDM tools
Not Rated

Matillion Support

Overall, I've found Matillion to be responsive and considerate. I feel like they value us as a customer even when I know they have customers who spend more on the product than we do. That speaks to a motive higher than money. They want to make a good product and a good experience for their customers.

If I have any complaint, it's that support sometimes feels community-oriented. It isn't always immediately clear to me that my support requests are going to a support engineer and not to the community at large. Usually, though, after a bit of conversation, it's clear that Matillion is watching and responding. And responses are generally quick in coming.
Good followup
Knowledgeable team
Problems get solved
Kept well informed
No escalation required
Support understands my problem
Support cares about my success
Quick Initial Response
At one point, we were evaluating a decision to move to the next tier of Matillion. This would have doubled our costs, but would also have given us access to more computing resources.

I can imagine that many vendors would have seen this as an upsell opportunity and done all in their power to make a case for upgrading. When I spoke with Matillion, though, they carefully went through our usage with us before making any recommendation. After we looked through our use cases and usage with them, they recommended we stay at the current tier. It was clear that we wouldn't get enough benefit from an upgrade to warrant the cost.

I appreciate that Matillion valued our business and the benefits we get from their product more than making a quick buck.