We performed a comparison between IBM Cloud Pak for Data and TIBCO Cloud Integration based on real PeerSpot user reviews.
Find out what your peers are saying about Denodo, SAP, IBM and others in Data Virtualization."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."
"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."
"The most valuable features are data virtualization and reporting."
"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."
"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."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."
"I like that it is a very good integration tool with many other things. TIBCO is very good for cloud integration"
"The product's initial setup phase was easy."
"I am really impressed by TIBCO's integration of any level of complexity."
"The solution's user experience is an area that has room for improvement."
"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 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 solution could have more connectors."
"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."
"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 deployment was rather complicated."
"TIBCO Cloud Integration is not a user-friendly tool when it comes to the installation phase or for maintaining the systems since its architecture is really complex."
"Integrations could be better. Although integration is good, we have faced some block issues."
IBM Cloud Pak for Data is ranked 3rd in Data Virtualization with 11 reviews while TIBCO Cloud Integration is ranked 17th in Integration Platform as a Service (iPaaS) with 3 reviews. IBM Cloud Pak for Data is rated 8.0, while TIBCO Cloud Integration is rated 8.4. 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 TIBCO Cloud Integration writes "A product that is easy to install and offers good stability to users". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Denodo, whereas TIBCO Cloud Integration is most compared with Azure Data Factory, Microsoft Azure Logic Apps and SAP Process Orchestration.
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.
