We performed a comparison between IBM Cloud Pak for Integration and Pentaho Data Integration and Analytics 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 aspect of the Cloud Pak, in general, is the flexibility that you have to use the product."
"Cloud Pak for Integration is definitely scalable. That is the most important criteria."
"It is a stable solution."
"The most preferable aspect would be the elimination of the command, which was a significant improvement. In the past, it was a challenge, but now we can proceed smoothly with the implementation of our policies and everything is managed through JCP. It's still among the positive aspects, and it's a valuable feature."
"Provides a good open source option."
"I can create faster instructions than writing with SQL or code. Also, I am able to do some background control of the data process with this tool. Therefore, I use it as an ELT tool. I have a station area where I can work with all the information that I have in my production databases, then I can work with the data that I created."
"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."
"The abstraction is quite good."
"The area where Lumada has helped us is in the commercial area. There are many extractions to compose reports about our sales team performance and production steps. Since we are using Lumada to gather data from each industry in each country. We can get data from Argentina, Chile, Brazil, and Colombia at the same time. We can then concentrate and consolidate it in only one place, like our data warehouse. This improves our production performance and need for information about the industry, production data, and commercial data."
"I can use Python, which is open-source, and I can run other scripts, including Linux scripts. It's user-friendly for running any object-based language. That's a very important feature because we live in a world of open-source."
"The amount of data that it loads and processes is good."
"It's very simple compared to other products out there."
"Setting up Cloud Pak for Integration is relatively complex. It's not as easy because it has not yet been fully integrated. You still have some products that are still not containerized, so you still have to run them on a dedicated VM."
"Its queuing and messaging features need improvement."
"The pricing can be improved."
"The initial setup is not easy."
"As far as I remember, not all connectors worked very well. They can add more connectors and more drivers to the process to integrate with more flows."
"Some of the scheduling features about Lumada drive me buggy. The one issue that always drives me up the wall is when Daylight Savings Time changes. It doesn't take that into account elegantly. Every time it changes, I have to do something. It's not a big deal, but it's annoying."
"I would like to see support for some additional cloud sources. It doesn't support Azure, for example. I was trying to do a PoC with Azure the other day but it seems they don't support it."
"There is not a data quality or MDM solution in the Pentaho DI suite."
"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'm still in the very recent stage concerning Pentaho Data Integration, but it can't really handle what I describe as "extreme data processing" i.e. when there is a huge amount of data to process. That is one area where Pentaho is still lacking."
"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."
"The testing and quality could really improve. Every time that there is a major release, we are very nervous about what is going to get broken. We have had a lot of experience with that, as even the latest one was broken. Some basic things get broken. That doesn't look good for Hitachi at all. If there is one place I would advise them to spend some money and do some effort, it is with the quality. It is not that hard to start putting in some unit tests so basic things don't get broken when they do a new release. That just looks horrible, especially for an organization like Hitachi."
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IBM Cloud Pak for Integration is ranked 14th in Cloud Data Integration with 4 reviews while Pentaho Data Integration and Analytics is ranked 15th in Data Integration with 48 reviews. IBM Cloud Pak for Integration is rated 8.6, while Pentaho Data Integration and Analytics is rated 8.0. The top reviewer of IBM Cloud Pak for Integration writes "A hybrid integration platform that applies the functionality of closed-loop AI automation". 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 Integration is most compared with IBM App Connect, IBM API Connect, IBM DataPower Gateway, MuleSoft Anypoint API Manager and Microsoft Azure API Management, 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 Integration vs. Pentaho Data Integration and Analytics report.
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