Likelihood to Recommend It is very well suited for ETL on the cloud. Whenever there is something that can be accomplished with no code or little code, Matillion is a good tool. However, if your pipeline requires a lot of customizations, Matillion should be avoided.
Read full review When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
Read full review Pros We leveraged Matillion’s no-code principals to make data manipulation easy for our internal customers. People who don't know how to use SQL no longer need to. Everything in Matillion is self-explained with no or little coding. We connected Matillion to our data warehouse to allow people to read raw data, transform it, then write results back to their sandbox databases. The drag and drop component design allowed customers to create complex data models at the speed of thought without any risk to production data. With sharing capabilities between projects enabled, everyone was able to help each other when questions arose which instilled a strong sense of collaboration and community. Read full review SAS/Access is great for manipulating large and complex databases. SAS/Access makes it easy to format reports and graphics from your data. Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs. Read full review Cons I think a non-CLI approach to installing and uninstalling python libraries would be nice. I mean, it isn't difficult to install a python library via Linux or CLI, but I imagine most companies don't feel comfortable allowing Matillion users to go on a virtual server and installing it themselves. Requirement.txt file for installing libraries would be simple, and maybe that could also be used to uninstall libraries as well......or maybe the library gets automatically downloaded if it is imported into a python script but the library doesn't exist. Python Component is lacking very much in terms of UI. It would be unrealistic for me to suggest Matillion build its own EDI, but it would be nice if a python component could connect to a local IDE. Right now, if you want to write any decent length python code, you are going to be stuck copying and pasting your code from your local IDE. It is also very difficult to debug in Matillion because you can't set breakpoints. Local IDE integration can resolve that. I would like to have more templates to copy from for certain simplistic scenarios. For instance, a template for a job that fails which sends an AWS SNS with the Job name, component it failed on, and the error message. It wasn't as simple as I thought it would be to figure out and having to use a shared job for such circumstances can be painful because you have to export a bunch of variables. There should be a drop down list for Global Matillion variables as it is difficult to remember at times. Read full review Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres. Debugging errors from the logs is a complicated process. E-mail alert system is very primitive and needs customization to make it more modern, Cannot send SMS alerts for jobs. Read full review Likelihood to Renew With the current experience of Matillion, we are likely to renew with the current feature option but will also look for improvement in various areas including scalability and dependability. 1. Connectors: It offers various connectors option but isn't full proof which we will be looking forward as we grow. 2. Scalability: As usage increase, we want Matillion system to be more stable.
Read full review We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
Read full review Usability It has been easy to train new employees who don't have previous experience with Matillion. It is quite self-explanatory. There are quite a few things that can be done with Python, however, we have not really looked into this feature much but likely will do in the future. Mostly, it is drag and drop of components and environments can be set up so easy to set up connections as well.
Read full review The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
Read full review Performance It worked as expected.
Read full review Support Rating 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.
Read full review With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
Read full review Implementation Rating We were able to control on access and built various enviroment for implementation
Read full review Alternatives Considered Matillion ran circles around Stitch and
Striim both in functionality, setup, and performance. There was no real comparison.
Fivetran massively outperforms Matillion in pretty much every facet of the production from setup, maintenance, visibility, and usability. It already has the ability to connect any data source to a destination regardless of database type. Why we chose Matillion over
Fivetran is that, for our current needs, Matillion provides us with the functionality that we need and a much more competitive price for a smaller company.
Read full review Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
Read full review Scalability I have been able to connect Matillion to AWS Aurora Databases, MySQL databases, Rest APIs, Files in AWS S3, etc. Being able to load all of that disparate data into one datalake has made data mining and reporting a lot simpler. I wish everything could be implemented as easily as Matillion.
Read full review Return on Investment Saving us time reduces our need for headcount Allows us to collaborate on data-eng pipelines in a transparent way with non-technical stakeholders, ensuring accuracy and continuity Allows us a single platform to log and manage all of our pipelines to pin-point where something failed and why Always has a solution to very common data engineering tasks, i.e., real-time data, connectors, pre-built workflows, etc. Read full review We have more users who can connect to the many different data sources. Our users do have existing SAS programming knowledge and that can carry over. Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction. Read full review ScreenShots