We performed a comparison between IBM Cloud Pak for Data and Palantir Foundry 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."
"Its data preparation capabilities are highly valuable."
"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."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"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."
"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."
"Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration."
"The security is also excellent. It's highly granular, so the admins have a high degree of control, and there are many levels of security. That worked well. You won't have an EDC unless you put everything onto the platform because it is its own isolated thing."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"The ease of use is my favorite feature. We're able to build different models and projects or combine different projects to build one use case."
"The interface is really user-friendly."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"It's scalable."
"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 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."
"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 solution's user experience is an area that has room for improvement."
"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 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 workflow could be improved."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"The solution's visualization and analysis could be improved."
"If you want to create new models on specific data sets, computing that is quite costly."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"Some error messages can be very cryptic."
"The solution could use more online documentation for new users."
"They do not have a data center in Europe, and we have lots of personally identifiable information in our dataset that needs to be hosted by a third-party data center like Amazon or Microsoft Azure."
IBM Cloud Pak for Data is ranked 16th in Data Integration with 11 reviews while Palantir Foundry is ranked 11th in Data Integration with 14 reviews. IBM Cloud Pak for Data is rated 8.0, while Palantir Foundry is rated 7.6. 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 Palantir Foundry writes "The data visualization is fantastic and the security is excellent". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Denodo and IBM InfoSphere Information Server, whereas Palantir Foundry is most compared with Azure Data Factory, Palantir Gotham, SAP Data Services, AWS Glue and BCG Big Data & Advanced Analytics. See our IBM Cloud Pak for Data vs. Palantir Foundry report.
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