We performed a comparison between IBM Cloud Pak for Data and Informatica Data Integration Hub based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."DataStage allows me to connect to different data sources."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"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."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"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."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"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."
"Performance and flexibility-wise, they're very user-friendly."
"The MDM solution is capable of integrating multiple systems, so it helped us to solve the purpose of centralizing the depository as well as the standardization of mass data. It takes away all the ambiguity around data integrity issues or all the process challenges which happen when every stage of a process uses a different source as master data."
"The technical support services are good."
"The technical support could be a little better."
"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."
"The product must improve its performance."
"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 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."
"The solution's user experience is an area that has room for improvement."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"The initial setup was not very straightforward. Not complex, but not very simple either."
"They could provide more robust performance for data integration processes. It would help in improving the data quality more efficiently."
"When it comes to UI look and feel and user experience, Informatica is not as good as other solutions."
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IBM Cloud Pak for Data is ranked 17th in Data Integration with 11 reviews while Informatica Data Integration Hub is ranked 37th in Data Integration with 3 reviews. IBM Cloud Pak for Data is rated 8.0, while Informatica Data Integration Hub is rated 8.0. 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 Data Integration Hub writes "Excellent at standardizing mass data and capable of integrating with multiple solutions ". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Denodo, whereas Informatica Data Integration Hub is most compared with Informatica PowerCenter, AWS Database Migration Service, Azure Data Factory, SAP Data Hub and Mule Anypoint Platform. See our IBM Cloud Pak for Data vs. Informatica Data Integration Hub report.
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We monitor all Data Integration 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.
