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.
"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."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"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."
"Its data preparation capabilities are highly valuable."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"I am impressed with the tool's ETL tracing."
"Highly customizable: Allowing you to handle multiple data latencies (scheduled batch, on-demand, and real-time) in the same job."
"IBM is stable and accurate to monitor. It's easy to understand to monitor the data lineage from source to target."
"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."
"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 product is a stable and powerful data management solution that can run in parallel mode for enhanced speed."
"As a data integration platform, it is easy to use. It is quite robust and useful for volumetric analysis when you have huge volumes of data. We have tested it for up to ten million rows, and it is robust enough to process ten million rows internally with its parallel processing. Its error logging mechanism is far simpler and easier to understand than other data integration tools. The newer version of InfoSphere has the data catalog and IDC lineage. They are helpful in the easy traceability of columns and tables."
"The solution's scalability is really good...we are using multi-instance jobs where you can scale them easily."
"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."
"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 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."
"The solution could have more connectors."
"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."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"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 response time from support is slow and needs to be improved."
"The troubleshooting guide is very bad."
"The documentation and in-application help for this solution need to be improved, especially for new features."
"The setup is extremely difficult."
"Its documentation is not up to the mark. While building APIs, we had a lot of problems trying to get around it because it is not very user-friendly. We tried to get hold of API documentation, but the documentation is not very well thought out. It should be more structured and elaborate. In terms of additional features, I would like to see good reporting on performance and performance-tuning recommendations that can be based on AI. I would also like to see better data profiling information being reported on InfoSphere."
"The pricing should be lower."
"I really like this tool, but the administration should be on the same client application because a lot of administration features are not on the client-side, and they usually need to have administrative access. It's quite complicated to force IT teams to have separate administrative access from the developers."
"In the future, I would like to see more integration with cloud technologies."
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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