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.
"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."
"Scalability-wise, I rate the solution a nine or ten 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 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."
"Its data preparation capabilities are highly valuable."
"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."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"It is quite useful and powerful."
"We like the flexibility of modeling."
"I am impressed with the tool's ETL tracing."
"The concept of integration is a valuable feature of the product."
"The product is a stable and powerful data management solution that can run in parallel mode for enhanced speed."
"We are mostly using transmission rules. It has a lot of functions and logic related to transmission. It is a user-friendly tool with in-built functions."
"Compared to other ETL tools, DataStage has excellent debugging and development capabilities. And the availability of connectors, even though we sometimes have to opt for specific ones. Also, the availability of patches is good."
"The data lineage report can be filtered for reporting. The reports are user-friendly and take less time to find what you need."
"The solution's user experience is an area that has room for improvement."
"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."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"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 technical support could be a little better."
"It would be useful to provide support for Python, AR, and Java."
"Currently lacking virtualization ability."
"I'd like to be able to do more with the data and metadata, including copy and pasting, et cetera."
"DataStage is quite expensive. It is too hard to find a consultant using DataStage in Turkey."
"The initial setup can be complex."
"In terms of intermediate storage, we have some challenges, especially with customers who store data in intermediate locations."
"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."
"The interface needs improvement."
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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