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."The most valuable features of Denodo are the extraction option for adapters, and there are many things for the views, that are cached. Denodo is not storing the data, it looks first to tune the query, and these things are for the agents."
"The logical data warehouse functionality is fantastic. It truly stands out. The ClearOptimizer and Virtual Cache are great features. They work together seamlessly to optimize performance."
"It is easy to virtualize data using the solution."
"The most valuable feature is Data Catalogs."
"The data abstraction is the most valuable feature."
"The most valuable aspects of this solution are the short time frame in which you can deliver and connect."
"It is a go-to tool for data virtualization. The virtualization and data catalog are the features of why we chose Denodo."
"It allows a lot of traceability and you can decide what data you want to collect"
"Pentaho Data Integration is quite simple to learn, and there is a lot of information available online."
"It's very simple compared to other products out there."
"The amount of data that it loads and processes is good."
"The graphical nature of the development interface is most useful because we've got people with quite mixed skills in the team. We've got some very junior, apprentice-level people, and we've got support analysts who don't have an IT background. It allows us to have quite complicated data flows and embed logic in them. Rather than having to troll through lines and lines of code and try and work out what it's doing, you get a visual representation, which makes it quite easy for people with mixed skills to support and maintain the product. That's one side of it."
"We can schedule job execution in the BA Server, which is the front-end product we're using right now. That scheduling interface is nice."
"It has a really friendly user interface, which is its main feature. The process of automating or combining SQL code with some databases and doing the automation is great and really convenient."
"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."
"The abstraction is quite good."
"The solution is slow when there are many virtualization layers."
"It would be good if the solution provided a much-needed cellular platform."
"User-specific security at the column and row levels needs to be improved. Instead of applying security at every individual level, it would be better if it were at the group or tier level. It will save a lot of time."
"The support is not the best and should be improved."
"I would like to see a connectivity option with third-party apps, for example, JDBC, and ODBC drivers. Currently, we need to install it separately from the Denodo side and then connect it."
"There have been some issues when you are at a table. Currently, Denodo exports data sets for a tabular model. When you are finished modeling your database or data warehouse they export a link to be used in Tableau. They should support other tools like Power BI."
"I would like it if we could pull the data model or export the data model because Denodo has, based on how you build, something called associations. The data model gets very confusing when you go look at it. It depends on how you define it, but it's really huge. I wish there was a way to export it into Visio. It could be that they already have a way to do it, and I don't know, but it would be much easier for the architects and even for the developers to look at it than scrunching it into the screen and expanding every small portion of it. If there was an easy way to export the Denodo model into another modeling tool and view it, it would be great."
"Lacks integrations with AWS, GCP and the like."
"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..."
"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."
"Parallel execution could be better in Pentaho. It's very simple but I don't think it works well."
"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."
"The product needs more plugins."
"Although it is a low-code solution with a graphical interface, often the error messages that you get are of the type that a developer would be happy with. You get a big stack of red text and Java errors displayed on the screen, and less technical people can get intimidated by that. It can be a bit intimidating to get a wall of red error messages displayed. Other graphical tools that are focused at the power user level provide a much more user-friendly experience in dealing with your exceptions and guiding the user into where they've made the mistake."
"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 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."
More Pentaho Data Integration and Analytics Pricing and Cost Advice →
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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