We performed a comparison between IBM Cloud Pak for Data and SAS Access based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."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."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"DataStage allows me to connect to different data sources."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"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 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."
"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 part of SAS/ACCESS is what it is made for: connecting to remote systems that are not part of your physical SAS environment."
"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."
"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 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 product must improve its performance."
"The solution could have more connectors."
"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."
"The solution can provide access to the newer databases that come out sooner."
IBM Cloud Pak for Data is ranked 15th 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, SSIS, Zapier and Toad Data Point.
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