We performed a comparison between IBM Cloud Pak for Data and WhereScape RED 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."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."
"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."
"Its data preparation capabilities are highly valuable."
"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."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"DataStage allows me to connect to different data sources."
"RED generates comprehensive documentation and regenerates it as quickly as things changes, but it also provides impact documentation."
"Naturally produces a way to easily debug your DW data solutions."
"Data transformations and rollups are easy to accomplish."
"Their support staff are very knowledgeable, courteous, and professional. I feel their support staff go above and beyond to assure their customers are satisfied."
"Support is absolutely excellent, efficient, and timely."
"I like the data vault implementations."
"It has a built-in automatic scheduling environment."
"WhereScape's deployment package is a fantastic feature. The application allows for selecting specific objects that you would like to deploy from one environment to another rather than deploying the entire database."
"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 product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"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 solution's user experience is an area that has room for improvement."
"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 technical support could be a little better."
"Technical support isn't the best."
"The ability to execute SSIS projects within WhereScape would be nice because we have a lot of packages that are too cumbersome to recreate."
"Jobs cannot be deleted via the deployment package. When deploying from dev to QA or production, a job has to be retired. The job has to be manually removed from the target environment."
"The solution can be a little more user-friendly on enterprise-level where people use it."
"It could use a tool to diagnose what is missing from the environment for WhereScape to install successfully."
"Customization could be better."
"Project-based searching of data objects in the data warehouse browser needs to be improved."
"The scheduled jobs which are run by the WhereScape scheduler seem to be a strangely separate animal. Unlike all other WhereScape objects, jobs cannot be added to WhereScape projects. Also, unlike all other objects, jobs also cannot be deleted using a WhereScape deployment application."
Earn 20 points
IBM Cloud Pak for Data is ranked 17th in Data Integration with 11 reviews while WhereScape RED is ranked 48th in Data Integration. IBM Cloud Pak for Data is rated 8.0, while WhereScape RED is rated 8.2. 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 WhereScape RED writes "Quick to set up, flexible, and stable". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Denodo, whereas WhereScape RED is most compared with Azure Data Factory, Informatica PowerCenter, SSIS, Matillion ETL and Denodo. See our IBM Cloud Pak for Data vs. WhereScape RED report.
See our list of best Data Integration vendors.
We monitor all Data Integration 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.
