Item: Matillion
Rating: 8
Author: Verified User

Overall Satisfaction with Matillion

Use Cases and Deployment Scope

Data extraction and loading from operational systems into the central data warehouse and data transformation. Automation of the loading and transformation jobs. It achieves the vision of combining all data for analysis and reporting in a central data warehouse in the cloud (Snowflake). It is easy to learn with the UI components to do standard transformation tasks, but it also allows coding logic in SQL or Python for more complex tasks that cannot be achieved with the pre-built components.

Pros and Cons

Pros

Orchestration and automation of data loading and transformation jobs.
Very cost efficient.
Easy to learn.

Cons

Configuring data extraction and loading jobs is a bit tedious.
Occasional out of memory errors due to Java (Tomcat) being used internally.
User administration and fine-granted permission control.

Return on Investment

Ability to combine data from multiple source systems.
Ability to create complete transparency about our metrics and how they are calculated from source to final report ( increase trust).
Fully automate all data loading and transformation tasks so no repetitive work needs to be done manually.

Usability

Easy tasks are really easy, and complex tasks are still possible. With prior knowledge of general data warehousing principles and experience with other data transformation tools, it's straightforward to get familiar with and use Matillion. I initially used minimal external support from a partner for some more complex tasks but very soon could work entirely independently with Matillion.

Time to Value

With prior knowledge of general data warehousing principles and experience with other data transformation tools, it's straightforward to get familiar with and use Matillion. I initially used minimal external support from a partner for some more complex tasks but very soon could work entirely independently with Matillion. It only took 2-4 weeks until the first productive data pipelines were in place and their results usable for reporting.

Scalability

It generally scales well for more jobs, people working with the tool, etc. In some cases, it had issues with large data volumes very well. For example, when working with custom API connectors to load data, We occasionally faced Java out-of-memory errors, which were hard to debug or resolve.

Alternatives Considered

Fivetran, dbt and Stitch from Talend

Fivetran offers a managed service and pre-configured schemas/models for data loading, which means much less administrative work for initial setup and ongoing maintenance. But it comes at a much higher price tag. So, knowing where your sweet spot is in the build vs. buy spectrum is essential to deciding which tool fits better. For the transformation part, dbt is purely (SQL-) code-based. So, it is mainly whether your developers prefer a GUI or code-based approach.

Key Insights

Do you think Matillion delivers good value for the price?

Yes

Are you happy with Matillion's feature set?

Yes

Did Matillion live up to sales and marketing promises?

Yes

Did implementation of Matillion go as expected?

Yes

Would you buy Matillion again?

Other Software Used

Snowflake, Fivetran, dbt

Likelihood to Recommend

If most of the operational systems to load data from are based in the cloud and you want to load the data into a cloud data warehouse, then Matillion is an excellent choice. If your developers prefer a GUI over code, then Matillion is a good choice. If you choose a single tool for loading the data into the data warehouse and the transformation part, then Matillion is a good choice. On the other hand, if your developers prefer to code or you prefer a best-of-breed approach for loading and transformation instead of the one-platform approach, then Matillion is less suited for you.

Matillion Feature Ratings

Comments

Please log in to join the conversation

Good value for money.