We performed a comparison between IBM Cloud Pak for Data and SAP HANA 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 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."
"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 are data virtualization and reporting."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"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."
"Its data preparation capabilities are highly valuable."
"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 solution is stable."
"I like the integration process. Also, the data is trusted by our management, and we use the data from transactions for analysis."
"The solution is marvelous because it controls everything including workflow and that makes our company more productive."
"It's easy to use, and the Hana Studio is pretty good."
"The performance in terms of processing time is unmatched due to the in-memory processing capability."
"The feature I found most valuable in SAP HANA is modeling. I also like that the solution has good integration and you can integrate it with any system, even third-party systems."
"Some functions have good performance."
"The initial setup is straightforward. It usually takes around eight months but it depends on a customer's requirements. We can spend a month or two customizing."
"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 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 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."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"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."
"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 improve in the handling of backup data and the administration tools."
"Ease of use could be improved in SAP HANA. I like SAP because SAP solutions can be used by anyone, which means even laymen can start working on SAP tools, but in SAP HANA modeling, you'll need to know some other technologies and sequel scripting, and you need a separate skillset, so if you don't have the skillset, you won't be able to work on SAP HANA. Making SAP HANA low-code would make it even better."
"Uses a large amount of RAM and is costly."
"There are a few areas wherein there could be a patch upgrade, and that can cover up the country-specific payroll areas."
"They should develop and improve the solution's data management system."
"The surface side or Attack dashboard needs improvement because there are some gaps after sales services."
"The high price of the product is an area of concern where improvements are required."
"I would like to see improvement on the feedback from the road-map; it is currently extremely hard to get insight in this area."
IBM Cloud Pak for Data is ranked 3rd in Data Virtualization with 11 reviews while SAP HANA is ranked 2nd in Data Virtualization with 81 reviews. IBM Cloud Pak for Data is rated 8.0, while SAP HANA 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 SAP HANA writes "Excellent compatibility between modules and the control". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Informatica PowerCenter, whereas SAP HANA is most compared with Oracle Database, SQL Server, MySQL and IBM Db2 Database. See our IBM Cloud Pak for Data vs. SAP HANA report.
See our list of best Data Virtualization vendors.
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.