Item: Matillion
Rating: 3
Author: Verified User

Overall Satisfaction with Matillion

Use Cases and Deployment Scope

We used Matillion for a little more than a year to ingest and historize data coming from SaaS tools and internal databases to a Snowflake datawarehouse. This data was then further transformed to build business actionnable data assets modeling the performance and operations of the company at large. Those assets help stakeholders across the business in taking data driven decisions

Pros and Cons

Pros

Salesforce native connector to ingest its data to Snowflake
Postgres native connector to ingest its data to Snowflake
Workday connector to ingest its data to Snowflake

Cons

In my experience, no code user interface is painful to use
In my experience, tool works for very simple use cases but doesn't support implementing complex workflows
In my experience, no testing capabilities
In my opinion, has the downsides of a SaaS (cost, low flexibility) and the downsides of self hosted (has to be hosted on customer infrastructure, handle updates...)
In my experience, unreactive customer service
In my experience, doesn't scale to high volumes of data
In my opinion, high maintenance costs of no code pipelines

Return on Investment

slowed us down on delivery compared to using custom code
big annual contract spend compared to value extracted
had to migrate away from it after a year

Usability

While Matillion's no-code features seem both useful and easy to use at first glance, in my experience, the reality quite differs from it. UI is sometimes buggy, it's hard to understand how some component works. Moreover the poor git integration doesn't bode well with having multiple people using the tool at the same time.

Time to Value

After running a POC of the tool for a month and a half, my team decided to move forward with a contract. The implementation part was pretty quick and well handled by Matillion implementation team. After a few weeks we were able to have a few pipelines running daily and feeding our datawarehouse.

Scalability

As we had the PaaS flavor of Matillion, our instance was hosted on an AWS EC2 instance that doesn't scale well. We had to pay for a big instance 24/7 while big workflows were only running for one hour a day. However when they did, we sometime saw the instance crash due to out of memory errors.

Alternatives Considered

Fivetran, Airbyte and Azure Data Factory

We decided to move forward with Matillion because it was the best tool among tools that support both ingesting data from a source system to a target database and running transformation workflows on it afterwards. Fivetran and Airbyte only support data ingestion and we had our infrastructure on AWS, not Azure.

Key Insights

Do you think Matillion delivers good value for the price?

Are you happy with Matillion's feature set?

Did Matillion live up to sales and marketing promises?

Did implementation of Matillion go as expected?

Would you buy Matillion again?

Other Software Used

dbt, Snowflake, Amazon Elastic Compute Cloud (EC2)

Likelihood to Recommend

Matillion is well suited for very straightforward data ingestion use cases from a system for which Matillion has a native connector or a simple REST API. It can prove useful in a team with low engineering skills thanks to its no code interface.
It is not appropriate for more complex use cases and teams which have engineering skills.

Matillion Feature Ratings

Comments

Please log in to join the conversation

Lucy Smith
(Vendor Representative) commented a year ago
Thank you for your detailed feedback. We're sorry to hear that your experience with Matillion didn't meet your expectations. Your insights, particularly regarding the UI, scalability, and maintenance costs, are invaluable to us as we strive to improve. We would greatly appreciate the opportunity to discuss your concerns further. Please message us so we can address your issues and find a solution.

Matillion no-code features, from dream to tragedy