Adverity vs. Maia by Matillion vs. Red Hat JBoss Data Virtualization

If you're a marketing organization that wants to own your data architecture, get away from hours of manual excel work, and build a flexible and scalable BI practice for yourself and your clients, Adverity is your solution. Especially if you don't have a dedicated analytics team or current database solution. If you have access to a wide variety of API's and a fully staffed team to custom develop new connectors in under 30 days for no incremental cost, you're probably best in-housing

Incentivized

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

I think it would work well in a Java/Linux environment. It is not as suited to Windows/.Net.

Incentivized

• Customizable dashboards, that you could change and make unique to your specific need / business.
• Combining a range of data sets into one view.
• Easily sharable insights, that you can share internally or also with clients.

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

• Data source compatibility: since it is Java, it can connect to anything with a JDBC driver.
• Flexibility: you can configure it however you want, we have it configured to use LDAPS for authentication and have all interfaces encrypted, and setting that up was pretty straight forward.

Incentivized

• Adverity is running into some issues being able to custom-develop API connectors at scale/speed. This is mostly because of their rapid growth and incredible core product. If you need custom development, be prepared to use one of the many easy-to-use workarounds Adverity offers for endpoints they don't have a direct integration with. Don't worry - you'll get your data either way.

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

• Pricing
• User Interface

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

Adverity is easy to understand and use, even for users who are less technical. Reports and dashboards are easy to send out, and back-end users can easily navigate workspaces for creating new data fetches.

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.

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Support availability and resolution response time make it a better choice.

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

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Previously I had never really used a tool like this, only using software such as GA to look at any insights and review performance. So I think that the combined view of having all of the data sets (Which in my role I wouldn't always particularly have access to), was really useful. As an individual who was optimising our clients websites it meant that I was really able to prioritise what was important, but also have a great view of absolutely all activity that was happening

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.

Market value and support extended by Redhat is the winner against Veritas. It has cool features and functionality but still, if your organization is Redhat shop it's better to go for the Jboss option.

Incentivized

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

• Scale - the biggest advantage has been the ability to extract, transform, and load data for 150+ clients with a three-person team without a software or data engineering team to support. Adverity would easily allow us to scale up to double or triple the client load if needed.
• Templates - Another advantage related to scale, Adverity allows us to run a templated approach to extraction, transformation, and also data visualization and reporting so that onboarding is very fast. Typical clients with up to 15 data sources can be onboarded in as little as a couple of hours.

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

• Flexibility
• Cost is not effective

Incentivized