We performed a comparison between IBM Cloud Pak for Data and SAS Access 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."You can model the data there, connect the data models with the business processes and create data lineage processes."
"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."
"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."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"DataStage allows me to connect to different data sources."
"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."
"The most valuable features are data virtualization and reporting."
"The most valuable aspect of the solution is the ease of access to the data in those databases."
"The most valuable feature is you have native access to the external databases."
"The most valuable part of SAS/ACCESS is what it is made for: connecting to remote systems that are not part of your physical SAS environment."
"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."
"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 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."
"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."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"The solution can provide access to the newer databases that come out sooner."
"The pricing model needs to be reconsidered and adjusted."
"I can't really recall any missing feature or general improvement that is needed. We don't really add too many new kinds of databases and therefore our needs are already met."
IBM Cloud Pak for Data is ranked 17th in Data Integration with 11 reviews while SAS Access is ranked 42nd in Data Integration with 3 reviews. IBM Cloud Pak for Data is rated 8.0, while SAS Access is rated 9.0. 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 SAS Access writes "The solution is stable, scalable, and flexible". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Denodo, whereas SAS Access is most compared with Delphix and Toad Data Point. See our IBM Cloud Pak for Data vs. SAS Access report.
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