Matillion has an easy learning curve and expansive customization options
May 25, 2019

Matillion has an easy learning curve and expansive customization options

Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Matillion

We use Matillion to support our recurring data requests and cleaning processes on large data sets. Approximately half of our department currently uses it.
  • The GUI is very intuitive, making it easy for new users while also having more complex functions available to experienced users.
  • There is a good mix of defined components and customization options, giving users flexibility for both their skill level and the task at hand.
  • Matillion includes a chron scheduler and s3 export options which streamline the process, enabling all portions of the ETL process to take place within the same utility.
  • Areas for improvement include local variable updates, e.g. a last run date.
  • More python library support would greatly broaden the potential uses.
  • The S3 export function could use some adjustments in making clear defaults, particularly in regards to snowflake file types.
  • Matillion has had a positive impact on our workflow and turn-around time, allowing the team to take on more and more complex projects.
Matillion has proven to have a solid combination of usability and customization options that make it useful for many diverse objectives.
I really don't have insight on scalability at this time, but I see no immediate hurdles.
I was not involved in the ETL tool search, but Matillion was selected for both usability and pricing options.
Matillion is well suited to recurring, SQL-based data pulls that happen on a regular basis. It is also easy to modify existing flows via variables for new tasks, as well as leveraging Python to update variables such as dates and date-based table names. It is not appropriate for live data return. "Select" is not supported in that data outputs must be sent to a table.

Matillion Feature Ratings

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