We performed a comparison between AWS Data Pipeline [EOL] and IBM InfoSphere DataStage based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of the solution is that orchestration and development capabilities are easier with the tool."
"It is a stable solution...It is a scalable solution."
"Highly customizable: Allowing you to handle multiple data latencies (scheduled batch, on-demand, and real-time) in the same job."
"It is quite useful and powerful."
"The Hierarchical Data Stage is good."
"The most valuable feature is the product's versatility to inject data."
"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."
"The solution has improved the time it takes to perform tasks related to batch applications."
"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."
"I am impressed with the tool's ETL tracing."
"It's almost semi-automatic because you must review and approve code push, which works well. Still, we had many problems getting there during the deployment process, but we got there."
"The user-defined functions have shortcomings in AWS Data Pipeline."
"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."
"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."
"The interface needs improvement."
"The troubleshooting guide is very bad."
"The graphical user interface (GUI) feels a lot like the interfaces from the 1980s."
"The interface needs work to be more user-friendly."
"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."
AWS Data Pipeline [EOL] doesn't meet the minimum requirements to be ranked in Cloud Data Integration with 2 reviews while IBM InfoSphere DataStage is ranked 7th in Data Integration with 37 reviews. AWS Data Pipeline [EOL] is rated 8.0, while IBM InfoSphere DataStage is rated 7.8. The top reviewer of AWS Data Pipeline [EOL] writes "A tool with great orchestration and development capabilities but needs to improve its user-defined functions". 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". AWS Data Pipeline [EOL] is most compared with AWS Database Migration Service, AWS Glue, Oracle Data Integrator (ODI), FME and IBM Cloud Pak for Integration, whereas IBM InfoSphere DataStage is most compared with SSIS, IBM Cloud Pak for Data, Azure Data Factory, Talend Open Studio and Informatica PowerCenter. See our AWS Data Pipeline [EOL] vs. IBM InfoSphere DataStage report.
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