We performed a comparison between Denodo and IBM Cloud Pak for Data based on real PeerSpot user reviews.
Find out in this report how the two Data Virtualization solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It is easy to virtualize data using the solution."
"In general, it's good for us to make tests so we can scout the data."
"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."
"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 very stable."
"The most valuable feature is the performance. Denodo is very useful, especially in this huge pharma environment. I've found that older SAP solutions were very tightly coupled to each other, which resulted in data restrictions. Getting data from different sources was tough and tedious. Compared to these old solutions, Denodo is very easy to work with for the analytical team. Now that we've implemented this virtualization layer, we are capable of getting the data very smoothly. We implemented a very small unit, but the performance and integration have been very good."
"The most valuable features are data lineage and the concept of a semantic layer."
"In PL/SQL, first you need to gather all the data and then start writing the file, but in Denodo you fetch the data and write the data simultaneously. So, for example, if you have 1 million or 2 million records, you don't have to wait to fetch all of the 2 million; you can keep on fetching and writing in the file simultaneously."
"Scalability-wise, I rate the solution a nine or ten out of ten."
"Its data preparation capabilities are highly valuable."
"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."
"DataStage allows me to connect to different data sources."
"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."
"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 solution is slow when there are many virtualization layers."
"The data catalog certainly has room for improvement. It is functional but we look forward to development. We are in constant contact with Denodo and they are fully aware of our needs."
"I would like to see a proper way to avoid killing the sourcing systems."
"Documentation needs to be improved"
"We would like this solution to be more universally user-friendly. At present it is really only aimed at IT specialists."
"We occasionally have some integration issues that we need to work through."
"It would be good if the solution provided a much-needed cellular platform."
"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."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"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."
"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."
"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 technical support could be a little better."
"The solution's user experience is an area that has room for improvement."
"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."
Denodo is ranked 1st in Data Virtualization with 29 reviews while IBM Cloud Pak for Data is ranked 3rd in Data Virtualization with 11 reviews. Denodo is rated 7.8, while IBM Cloud Pak for Data 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 IBM Cloud Pak for Data writes "A scalable data analytics and digital transformation tool that provides useful features and integrations". Denodo is most compared with Azure Data Factory, AWS Glue, Mule Anypoint Platform, Delphix and TIBCO Data Virtualization, whereas IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and IBM InfoSphere Information Server. See our Denodo vs. IBM Cloud Pak for Data report.
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