We performed a comparison between Azure Data Factory 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."This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The security of the agent that is installed on-premises is very good."
"The data copy template is a valuable feature."
"The function of the solution is great."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"The solution has a good interface and the integration with GitHub is very useful."
"We haven't had any issues connecting it to other products."
"The abstraction is quite good."
"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."
"It's very simple compared to other products out there."
"Sometimes, it took a whole team about two weeks to get all the data to prepare and present it. After the optimization of the data, it took about one to two hours to do the whole process. Therefore, it has helped a lot when you talk about money, because it doesn't take a whole team to do it, just one person to do one project at a time and run it when you want to run it. So, it has helped a lot on that side."
"Flexible deployment, in any environment, is very important to us. That is the key reason why we ended up with these tools. Because we have a very highly secure environment, we must be able to install it in multiple environments on multiple different servers. The fact that we could use the same tool in all our environments, on-prem and in the cloud, was very important to us."
"The amount of data that it loads and processes is good."
"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."
"Pentaho Data Integration is quite simple to learn, and there is a lot of information available online."
"The one element of the solution that we have used and could be improved is the user interface."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."
"When the record fails, it's tough to identify and log."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"Its basic functionality doesn't need a whole lot of change. There could be some improvement in the consistency of the behavior of different transformation steps. The software did start as open-source and a lot of the fundamental, everyday transformation steps that you use when building ETL jobs were developed by different people. It is not a seamless paradigm. A table input step has a different way of thinking than a data merge step."
"Since Hitachi took over, I don't feel that the documentation is as good within the solution. It used to have very good help built right in."
"It's not very stable, at least not in the case of the community edition. I'm working with the community edition right now and I think perhaps it is because of that it is not very stable, it causes the system to sometimes hang. I'm not sure if this is the case for pair tiers."
"I would like to see improvements made for real-time data processing."
"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."
"It could be better integrated with programming languages, like Python and R. Right now, if I want to run a Python code on one of my ETLs, it is a bit difficult to do. It would be great if we have some modules where we could code directly in a Python language. We don't really have a way to run Python code natively."
"I work with the Community Edition, therefore I do not have support. There was an issue that I could not resolve with community support."
"One thing that I don't like, just a little, is the backward compatibility."
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Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Pentaho Data Integration and Analytics is ranked 16th in Data Integration with 48 reviews. Azure Data Factory is rated 8.0, while Pentaho Data Integration and Analytics is rated 8.0. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". 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". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Pentaho Data Integration and Analytics is most compared with SSIS, Talend Open Studio, Oracle Data Integrator (ODI), AWS Glue and SAP Data Services. See our Azure Data Factory vs. Pentaho Data Integration and Analytics report.
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