We performed a comparison between IBM Cloud Pak for Data and Informatica Cloud Data Integration 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."The most valuable features are data virtualization and reporting."
"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."
"Its data preparation capabilities are highly valuable."
"The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"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."
"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."
"DataStage allows me to connect to different data sources."
"It is one of the best tools available for data integration."
"We have a lot of integrations, and it's very easy to create integrations. They have a lot of connectors."
"Their new licensing is very flexible. With Informatica Cloud, you have plenty of items under the same umbrella, such as services, offerings, data quality, and data masking. You have also got master data management and API management. What I really like about them is that you don't need to go to Informatica and say that you need a data integration module. You would say that you need iPaaS or Informatica Cloud. They'll then try to understand your needs and give you IPUs, which are the processing units. If I purchased a hundred IPUs from Informatica as a customer, I can use 70 IPUs for data integration. I would also need data quality, so I can use 10 IPUs for data quality. I can use the remaining 20 IPUs for API management. Down the line, if I see that my initial data integration needs for the development phase are met, then out of the 70 IPUs assigned for data integration, I can use 30 IPUs for data masking. I can shuffle these numbers in any way within the Informatica Cloud umbrella for the tenure for which I have subscribed to these IPUs. I can use all services the way I want. This flexibility is what I really love about Informatica. It also has got good connectors."
"The Mapping Configuration and PowerCenter wizards are valuable. We use them to run our business logic."
"The data mapping capability is a valuable feature."
"The solution's initial setup is quite straightforward."
"The solution has the best feature for parameterization."
"The solution provides increased efficiency while still being user-friendly and easy to operate."
"The solution could have more connectors."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"The technical support could be a little better."
"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 product must improve its performance."
"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."
"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."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"I have received feedback from certain teams and there is a steep learning curve to use this solution."
"User/group administration could use improvement."
"A general improvement in icons and the virtual interface would be good."
"The integration process is not easy."
"Certain shortcomings in the product's UI make it an area where improvements are required."
"I would also like to have profiling functionalities and quality transformations in the cloud."
"One area where Informatica Cloud Data Integration could improve is in providing more accelerators for certain functionalities."
"There are a small number of UI bugs that occur on occasion."
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IBM Cloud Pak for Data is ranked 3rd in Data Virtualization with 11 reviews while Informatica Cloud Data Integration is ranked 5th in Cloud Data Integration with 40 reviews. IBM Cloud Pak for Data is rated 8.0, while Informatica Cloud Data Integration is rated 7.8. 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 Informatica Cloud Data Integration writes "A stable, scalable, and user-friendly solution". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Palantir Foundry, Denodo and IBM InfoSphere Information Server, whereas Informatica Cloud Data Integration is most compared with Informatica PowerCenter, Azure Data Factory, AWS Glue, Fivetran and Oracle Integration Cloud Service. See our IBM Cloud Pak for Data vs. Informatica Cloud Data Integration report.
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