We performed a comparison between Alteryx Designer and IBM Cloud Pak for Data 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."Workflow automation, in general, is valuable."
"The most valuable features are the integrated properties and integrated connectivity."
"When you open a raw Excel file, it can be hard to look at everything in detail. Alteryx makes it much easier to go through the data, summarize it, and use different tools for analysis."
"It has an easy setup process."
"I believe in the ability to connect to multiple data sources, as well as the ease of use to transform data and output data in a variety of formats."
"It helps them to create customized workflows, transform data, perform calculations, and consolidate multiple data sources into a target database."
"Alteryx Designer's best features are that it's easy to use and performs well."
"The features I found most valuable are the preparation features – the Join and the Transform."
"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 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."
"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."
"The most valuable features are data virtualization and reporting."
"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."
"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."
"Alteryx's data science and machine learning capabilities are where it loses out to DataIQ."
"Alteryx Designer overall should be easier to use."
"The only thing is sometimes it can be a bit slow."
"Sometimes, while getting data from a third-party product, the solution works slowly."
"Optimizing processing times is one area I would like to see improved in Alteryx Designer. Sometimes, the workflows take an extremely long time to run. There are days when I have had to wait two to three hours for a single process to complete. There needs to be a functionality to split the processes."
"The actual usage part of it needs to be explained more. It's too vague right now."
"I would like to be able to include small snippets of code inside of the solution. The tool has only drag-and-drop features to make it easy to use, but sometimes I feel like this makes it more complicated."
"When it comes to the pivoting part, the drill-through option is not there in Alteryx."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"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 have more connectors."
"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 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."
Alteryx Designer is ranked 9th in Data Integration with 27 reviews while IBM Cloud Pak for Data is ranked 17th in Data Integration with 11 reviews. Alteryx Designer is rated 8.0, while IBM Cloud Pak for Data is rated 8.0. The top reviewer of Alteryx Designer writes "An easy-to-use automation solution with satisfying customer support". On the other hand, the top reviewer of IBM Cloud Pak for Data writes "A scalable data analytics and digital transformation tool that provides useful features and integrations". Alteryx Designer is most compared with Azure Data Factory, FME, Informatica PowerCenter, SSIS and Palantir Foundry, whereas IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and SAS Data Management. See our Alteryx Designer vs. IBM Cloud Pak for Data 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.