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 features are data virtualization and reporting."
"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."
"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."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"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."
"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"The solution has improved the time it takes to perform tasks related to batch applications."
"It's a robust solution."
"The most valuable feature is the product's versatility to inject data."
"ETL is the most valuable feature."
"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."
"When we have needed help from the IBM team, they were helpful. Our company is a premium partner so we get fast responses."
"I am impressed with the tool's ETL tracing."
"The performance optimization is quite good in DataStage. It provides parallelism and pipelining mechanisms"
"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 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."
"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 product must improve its performance."
"The solution could have more connectors."
"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."
"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 terms of intermediate storage, we have some challenges, especially with customers who store data in intermediate locations."
"The response time from support is slow and needs to be improved."
"The initial setup could be more straightforward."
"The template mapping could be easier."
"The solution can be a bit more user-friendly, similar to Informatica."
"So, there are some features that are missing. If I compare DataStage to Talend, Talend allows you to write custom code in Java or use these tools in your applications as well if you are building a job application. But in DataStage, it does not allow you to write custom code for any component."
"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."
IBM Cloud Pak for Data is ranked 16th 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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