We performed a comparison between IBM Cloud Pak for Data and Informatica PowerCenter based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Its data preparation capabilities are highly valuable."
"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."
"DataStage allows me to connect to different data sources."
"The most valuable features are data virtualization and reporting."
"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."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"I found the map links, work links, and workflows valuable. They are important features."
"The interface is very clean and clear."
"The most complex task, in this case, was to read and transform BLOB data, and Java transformation in Informatica Power Center was a great solution."
"The most valuable feature is the new Data Lake feature, which provides the basic capabilities needed."
"Informatica PowerCenter is a very good ETL tool."
"What I like most about Informatica PowerCenter is that it's the best tool in the market for data integration. Currently, I work in L'Oréal, where a new system from SAP is used. Informatica PowerCenter integration with SAP is very, very fast and very, very simple, so you have the server flow from SAP, and through Informatica PowerCenter, you can ingest the data and make that data available for the business more quickly."
"It is easy to use, and it is quick for developing things. It is fairly powerful, and it can integrate with a lot of different platforms without much hassle."
"I like the automated scheduling feature."
"The solution's user experience is an area that has room for improvement."
"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."
"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."
"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."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"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."
"Integrated Reporting service should be more smoothly transitioned from view to function to be in sync with the main design."
"If we could have the option of performance improvement within Informatica, and if it could have more features, that would be ideal."
"The developer tool documentation can be enhanced with a more clear explanation of each utility, accompanied by relevant examples, so that developers are able to create programs with ease."
"An issue which should be addressed is that the solution only allows us to do structured, as opposed to unstructured, data processing."
"They should release new versions for the solution's on-premises setup."
"As a connector to big data, it is not well developed. We've had problems connecting Informatica with Hadoop. The functionality to connect Informatica with Hadoop, for me it's not good."
"Informatica, in my opinion, is very rigid and not very flexible, whereas platforms like Alteryx or Matillion are very flexible and agile."
"The pricing could be improved."
IBM Cloud Pak for Data is ranked 17th in Data Integration with 11 reviews while Informatica PowerCenter is ranked 3rd in Data Integration with 78 reviews. IBM Cloud Pak for Data is rated 8.0, while Informatica PowerCenter is rated 8.0. 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 Informatica PowerCenter writes "Stable, provides good support, and integrating it with other systems is very fast, but its pricing is expensive". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Talend Data Fabric, whereas Informatica PowerCenter is most compared with Informatica Cloud Data Integration, Azure Data Factory, SSIS, Databricks and AWS Glue. See our IBM Cloud Pak for Data vs. Informatica PowerCenter report.
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