We performed a comparison between Denodo 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."Denodo's best features are its performance, easy data transformation, and the job scheduler."
"The most valuable aspects of this solution are the short time frame in which you can deliver and connect."
"The performance and the speed to market are the most valuable features of this solution."
"The most valuable features are data lineage and the concept of a semantic layer."
"Data mining is one of the valuable features. We're able to connect all of the data sources with the installed driver, so that is a good advantage in Denodo. Being able to join the tables and view them is also valuable."
"Denodo makes it easy to export data as a service or data link to other services."
"While we may not be using all the features of Denodo at this time, we have found the data virtualization features to be very useful in helping us connect our data sources together, bringing all our data into one platform."
"Denodo is lightweight in terms of how it leads you to combine your discrete data systems at one spot."
"Data transformation within Pentaho is a nice feature that they have and that I value."
"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."
"It's very simple compared to other products out there."
"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 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."
"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."
"We use Lumada’s ability to develop and deploy data pipeline templates once and reuse them. This is very important. When the entire pipeline is automated, we do not have any issues in respect to deployment of code or with code working in one environment but not working in another environment. We have saved a lot of time and effort from that perspective because it is easy to build ETL pipelines."
"We can't scale it to meet digital requirements."
"We occasionally have some integration issues that we need to work through."
"Denodo currently integrates with ChatGPT, but the ability to manage and utilize them directly within Denodo would be a significant improvement."
"It would be good if the solution provided a much-needed cellular platform."
"Denodo has some difficulty supporting large numbers of records."
"The feature that you have to connect on LDAP needs improvement."
"Denodo's training documentation could be improved by providing more material. From an administrative standpoint, I've found that only Denodo websites provide the usual tutorials. It may be because it's a bit of a restricted tool, but it results in trouble with learning. Normally, I can find help and solutions from other sources, but I haven't been able to find any for Denodo. Other that, it's fine and it performs well. I only have six months of experience, so I can't accurately suggest improvements."
"Denodo can improve usage management-related aspects. If you deal with the mini views, it gets stuck. The performance is very slow when we go with a large number of views and high volume."
"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."
"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."
"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."
"In terms of the flexibility to deploy in any environment, such as on-premise or in the cloud, we can do the cloud deployment only through virtual machines. We might also be able to work on different environments through Docker or Kubernetes, but we don't have an Azure app or an AWS app for easy deployment to the cloud. We can only do it through virtual machines, which is a problem, but we can manage it. We also work with Databricks because it works with Spark. We can work with clustered servers, and we can easily do the deployment in the cloud. With a right-click, we can deploy Databricks through the app on AWS or Azure cloud."
"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."
"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."
"The reporting definitely needs improvement. There are a lot of general, basic features that it doesn't have. A simple feature you would expect a reporting tool to have is the ability to search the repository for a report. It doesn't even have that capability. That's been a feature that we've been asking for since the beginning and it hasn't been implemented yet."
"I could not connect to our Hadoop environment in an easy and flexible way, and it was important to scale our data warehouse."
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Denodo is ranked 12th in Data Integration with 29 reviews while Pentaho Data Integration and Analytics is ranked 16th in Data Integration with 48 reviews. Denodo is rated 7.8, while Pentaho Data Integration and Analytics is rated 8.0. The top reviewer of Denodo writes "Saves our underwriters' time with data virtualization, but could provide more learning resources". 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". Denodo is most compared with Azure Data Factory, AWS Glue, Delphix, Mule Anypoint Platform and Informatica PowerCenter, whereas Pentaho Data Integration and Analytics is most compared with Azure Data Factory, SSIS, Talend Open Studio, Oracle Data Integrator (ODI) and AWS Glue. See our Denodo vs. Pentaho Data Integration and Analytics report.
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