Azure Data Box vs. Maia by Matillion

Great: Need to query simpler APIs, or utilize well known services such as GSheets etc.? Matillion has got some of the best and easiest to use connectors out there. Not so great: Do you need have a competent CI/CD flow that you will be able to update / compare from Matillion as well as other sources at the same time? Good luck, you will need to be extra careful, as you might have to have a deeper dive into your servers Terminal each time you have a git conflict.

Incentivized

• The user interface of your data pipelines makes it easier for people who aren’t as techy as data engineers to observe what's going on.
• Customer support is quick, not always as efficient as you would want it to be, but still.
• Nice documentation available.

Incentivized

• Static and monolithic, it will show its limits when running multiple concurrent jobs.
• Github and versioning implementation is messy and broken. Don't use it.
• There's not way to see/query the system resources, just wait for a server to crash due to out of memory. An admin panel would be appreciated + some env variables with updated info.
• API implementation is cumbersome and limited.
• There's no concept of hub and worker engine, everything happens of the same server (designing workflows and executing them). Having separate light ETL engines to run job could be better. (sort of docker/kubernetes/lambda functions).
• Handling of variables is limited especially for returned values from sub components.
• Some components could return more metadata at the end of their execution instead of the standard one.
• Billing is badly designed not taking into account that the server is hosted by the client. Expensive.
• We had several issue with migration where starting a new instance was required and then migrating the content. It was painful and time consuming also have to deal with support and engineering team on Matillion side.
• CDC doesn't work as expected or it is not a mature product yet.

Incentivized

Matillion is easy to use and flexible to debug. Performance are good and support is giving us a good service level. There are still some technical points to be developed more (such as SAP extraction). but easy flows are really fast to be developed. We are also using a tool for migration from other tools, and it is useful as Matillion is producing XML code.

Incentivized

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.

Incentivized

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.

Incentivized

We were able to control on access and built various enviroment for implementation

Incentivized

We selected Matillion primarily because of it's ability to connect to numerous data sources and easily create transformation jobs. While Fivetran does a better job managing and examining deltas, it is not easy to use and is very non user friendly. SSIS was not a good fit for our team and required a significant amount of attention and server management that we did not want to invest in.

We're using Matillion on EC2 instances, and we have about 20 projects for our clients in the same instance. Sometimes, we're struggling to manage schedules for all projects because thread management is not visible, and we can't see the process at the instance level.

Incentivized

• Time savings -- we could custom code nearly everything Matillion does, but it would take days/weeks instead of minutes/hours.
• There's a bit of a learning curve to truly unlock Matillion's potential, and that can be frustrating for some new users, but once you get over that curve, the possibilities are endless.
• It allows us to centralize the hundreds of way to bring data in, so that even if you have to troubleshoot what someone else wrote, it's easy to jump in and understand what is happening.

Incentivized