We compared IBM InfoSphere DataStage and IBM Cloud Pak for Data based on our user's reviews in several parameters.
IBM InfoSphere DataStage is praised for its strong data integration, connectors, workflow management, ETL functionalities, and data quality controls. In contrast, IBM Cloud Pak for Data is commended for its analytics capabilities, user interface, data management tools, integration, scalability, governance, security, collaboration, and AI-driven features. Feedback on customer service, setup duration, pricing, and ROI varies between the two products.
Features: IBM InfoSphere DataStage is praised for its strong data integration capabilities, comprehensive set of connectors, efficient workflow management, and robust ETL functionalities. On the other hand, IBM Cloud Pak for Data is valued for its robust analytics capabilities, ease of use, comprehensive data management tools, seamless integration, and advanced data governance and security features. It also offers AI-driven capabilities like machine learning and predictive analytics.
Pricing and ROI: The available data does not provide any information about the setup cost for IBM InfoSphere DataStage. Similarly, the pricing and licensing information for IBM Cloud Pak for Data is not provided in the available data source., IBM InfoSphere DataStage has no available data to determine its ROI, while there is also no information or insights about the ROI of IBM Cloud Pak for Data.
Room for Improvement: IBM InfoSphere DataStage does not have specific areas for improvement identified in the available responses. Similarly, there is no specific feedback or review available for IBM Cloud Pak for Data on what needs improvement.
Deployment and customer support: Based on the available summaries, it is not possible to compare the user reviews regarding the duration to establish IBM InfoSphere DataStage and IBM Cloud Pak for Data as the feedback related to these aspects is not provided for both products., Based on the available data, there is not enough information to provide a summary of the customer service and support of IBM InfoSphere DataStage. The customer service and support of IBM Cloud Pak for Data received a lack of feedback from the reviews provided.
The summary above is based on 24 interviews we conducted recently with IBM InfoSphere DataStage and IBM Cloud Pak for Data users. To access the review's full transcripts, download our report.
"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."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"DataStage allows me to connect to different data sources."
"The most valuable features are data virtualization and reporting."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"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."
"ETL is the most valuable feature."
"The solution is stable."
"The ETL tools are probably the most valuable feature. It has an IBM tool, a friendly UI and it makes things more comfortable."
"Offers great flexibility."
"The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms"
"The most valuable feature for our data processing needs is IBM InfoSphere DataStage's capability to handle ETL tasks with large record volumes."
"It's a robust solution."
"The best feature of IBM InfoSphere DataStage for me was that it was very much user-friendly. The solution didn't require that much raw coding because most of its features were drag and drop, plus it had a large number of functionalities."
"The product must improve its performance."
"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."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"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."
"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 could be more customization options for the product."
"There are three things that could improve - the cloud, monitoring and cloud integration. It's a solid product but not a modern one and of course it depends what you're looking for."
"The solution can be a bit more user-friendly, similar to Informatica."
"It takes a lot of time to actually trigger your job and then go into the logs and other stuff. So all of this is really time-consuming."
"The graphical user interface (GUI) feels a lot like the interfaces from the 1980s."
"The interface needs work to be more user-friendly."
"The pricing should be lower."
"Their web interface is good but the on-prem sites are outdated. The solution could also be improved if they could integrate the data pipeline scheduling part of their interface."
IBM Cloud Pak for Data is ranked 17th in Data Integration with 11 reviews while IBM InfoSphere DataStage is ranked 7th in Data Integration with 37 reviews. IBM Cloud Pak for Data is rated 8.0, while IBM InfoSphere DataStage is rated 7.8. 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 IBM InfoSphere DataStage writes "User-friendly with a lot of functions for transmission rules, but has slow performance and not suitable for a huge volume of data". IBM Cloud Pak for Data is most compared with Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry, Denodo and IBM InfoSphere Information Server, whereas IBM InfoSphere DataStage is most compared with SSIS, Azure Data Factory, Talend Open Studio, Informatica PowerCenter and IBM InfoSphere Information Server. See our IBM Cloud Pak for Data vs. IBM InfoSphere DataStage report.
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