We performed a comparison between IBM Cloud Pak for Data and Pentaho Data Integration and Analytics 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."Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"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."
"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."
"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."
"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."
"The most valuable features are data virtualization and reporting."
"The abstraction is quite good."
"One of the most valuable features is the ability to create many API integrations. I'm always working with advertising agents and using Facebook and Instagram to do campaigns. We use Pentaho to get the results from these campaigns and to create dashboards to analyze the results."
"It makes it pretty simple to do some fairly complicated things. Both I and some of our other BI developers have made stabs at using, for example, SQL Server Integration Services, and we found them a little bit frustrating compared to Data Integration. So, its ease of use is right up there."
"The fact that it's a low-code solution is valuable. It's good for more junior people who may not be as experienced with programming."
"Provides a good open source option."
"The way it has improved our product is by giving our users the ability to do ad hoc reports, which is very important to our users. We can do predictive analysis on trends coming in for contracts, which is what our product does. The product helps users decide which way to go based on the predictive analysis done by Pentaho. Pentaho is not doing predictions, but reporting on the predictions that our product is doing. This is a big part of our product."
"It's very simple compared to other products out there."
"The amount of data that it loads and processes is good."
"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."
"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 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."
"The solution's user experience is an area that has room for 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 solution could have more connectors."
"The product must improve its performance."
"I would like to see more improvements with AS400 DB2."
"I would like to see improvement when it comes to integrating structured data with text data or anything that is unstructured. Sometimes we get all kinds of different files that we need to integrate into the warehouse."
"Parallel execution could be better in Pentaho. It's very simple but I don't think it works well."
"The web interface is rusty, and the biggest problem with Pentaho is debugging and troubleshooting. It isn't easy to build the pipeline incrementally. At least in our case, it's hard to find a way to execute step by step in the debugging mode."
"I have been facing some difficulties when working with large datasets. It seems that when there is a large amount of data, I experience memory errors."
"I was not happy with the Pentaho Report Designer because of the way it was set up. There was a zone and, under it, another zone, and under that another one, and under that another one. There were a lot of levels and places inside the report, and it was a little bit complicated. You have to search all these different places using a mouse, clicking everywhere... each report is coded in a binary file... You cannot search with a text search tool..."
"I would like to see improvements made for real-time data processing."
"I work with different databases. I would like to work with more connectors to new databases, e.g., DynamoDB and MariaDB, and new cloud solutions, e.g., AWS, Azure, and GCP. If they had these connectors, that would be great. They could improve by building new connectors. If you have native connections to different databases, then you can make instructions more efficient and in a more natural way. You don't have to write any scripts to use that connector."
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IBM Cloud Pak for Data is ranked 17th in Data Integration with 11 reviews while Pentaho Data Integration and Analytics is ranked 15th in Data Integration with 48 reviews. IBM Cloud Pak for Data is rated 8.0, while Pentaho Data Integration and Analytics 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 Pentaho Data Integration and Analytics writes "It's flexible and can do almost anything I want it to do". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Denodo, whereas Pentaho Data Integration and Analytics is most compared with SSIS, Azure Data Factory, Talend Open Studio, Oracle Data Integrator (ODI) and AWS Glue. See our IBM Cloud Pak for Data vs. Pentaho Data Integration and Analytics report.
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