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.
"DataStage allows me to connect to different data sources."
"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."
"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."
"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."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"The solution is stable."
"Offers great flexibility."
"The solution is very easy to use."
"We like the flexibility of modeling."
"IBM is stable and accurate to monitor. It's easy to understand to monitor the data lineage from source to target."
"The data lineage report can be filtered for reporting. The reports are user-friendly and take less time to find what you need."
"The concept of integration is a valuable feature of the product."
"We can view what we want to do. We can transform data and put them on tables."
"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's user experience is an area that has room for improvement."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"The solution could have more connectors."
"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 technical support could be a little better."
"What needs improvement in IBM InfoSphere DataStage is its pricing. The pricing for the solution is higher than its competitors, so a lot of the clients my company has worked with prefer other tools over IBM InfoSphere DataStage because of the high price tag. Another area for improvement in the solution stems from a lot of new types of databases, for example, databases in the cloud and big data have become available, and IBM InfoSphere DataStage is working on various connectors for different data sources, but that still isn't up-to-date, meaning that some connectors are missing for modern data sources. The latest version of IBM InfoSphere DataStage also has a complex architecture, so my team faced frequent outages and that should be improved as well."
"The initial setup can be complex."
"The setup is extremely difficult."
"Improvements for DataStage could include better integration with modern data sources like cloud solutions and documents, along with enhancing its capability to handle non-structured data."
"Reduced cost would allow more customers to choose the product. It's quite expensive in relation to the cost of other similar solutions."
"We would be happy to see in next versions the ability to return several parameters from jobs. Now, jobs can return just one parameter. If they could return several parameters, that would be great."
"The interface needs improvement."
"I want the tool to continue with the on-prem version, not the cloud one."
IBM Cloud Pak for Data is ranked 15th 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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