We performed a comparison between IBM Cloud Pak for Data and Matillion ETL based on real PeerSpot user reviews.
Find out in this report how the two Data Virtualization solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Scalability-wise, I rate the solution a nine or ten out of ten."
"It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"The most valuable features are data virtualization and reporting."
"Its data preparation capabilities are highly valuable."
"DataStage allows me to connect to different data sources."
"The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"It takes less than five minutes to set up and delivers results. It is much quicker than traditional ETL technologies."
"The product has a good user interface."
"Matillion ETL is one hundred percent stable."
"We allow non-technical people to use Matillion to load data into our data warehouse for reporting. Thus, it is easy enough to use that we don't always have to get a technical person involved in setting up a data movement (ETL)."
"Matillion ETL helps manage data movement, ingestion, and transformation through pipelines."
"It can scale to a great extent. It can handle the load that we are putting on it, which is about 5TBs."
"It has good integrations with Amazon Redshift and other AWS services."
"It has helped us to get onto the cloud quickly."
"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."
"The product must improve its performance."
"The interface could improve because sometimes it becomes slow. Sometimes there is a delay between clicks when using the software, which can make the development process slow. It can take a few seconds to complete one action, and then a few more seconds to do the next one."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."
"The technical support could be a little better."
"The solution's user experience is an area that has room for improvement."
"The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer...So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support."
"Matillion’s on-premises capabilities don’t allow you to build something customized."
"The tool's lineage is very weak."
"Unlike Snowflake which automatically takes care of upgrading to the latest version and includes additional features, with Matillion ETL we need to do this ourselves."
"The improvement area could be possible if the tool provides better integration capabilities with other ecosystems, including governance tools or data cataloging tools, as it is currently an area where the solution is lacking."
"One of the features that's in development is data privacy in the cloud, along with further SAP integration. For connectivity to SAP systems."
"While the UI is good, it could be improved in its efficiency and made easier to use."
"It needs integration with more data sources."
"Going forward, I would like them to add custom jobs, since we still have to run these outside of Matillion."
IBM Cloud Pak for Data is ranked 3rd in Data Virtualization with 11 reviews while Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews. IBM Cloud Pak for Data is rated 8.0, while Matillion ETL is rated 8.6. The top reviewer of IBM Cloud Pak for Data writes "A scalable data analytics and digital transformation tool that provides useful features and integrations". On the other hand, the top reviewer of Matillion ETL writes "Efficient data integration and transformation with seamless cloud-native integration". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Denodo, whereas Matillion ETL is most compared with Snowflake, Azure Data Factory, AWS Glue, Informatica PowerCenter and SSIS. See our IBM Cloud Pak for Data vs. Matillion ETL report.
We monitor all Data Virtualization reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
