We performed a comparison between Denodo and SAP Data Hub based on real PeerSpot user reviews.
Find out what your peers are saying about Denodo, SAP, IBM and others in Data Virtualization."It allows a lot of traceability and you can decide what data you want to collect"
"Denodo is very stable."
"The most valuable feature is Data Catalogs."
"The most valuable features are query optimization and the single language independence from the sources we're using to catch data."
"It can support a number of data sources, and it can pull flat files, from cloud-based databases or from those on-premises. Denodo can pull from any data source and interface with the view. Then, we can publish the view."
"The performance and the speed to market are the most valuable features of this solution."
"Denodo's best features are its performance, easy data transformation, and the job scheduler."
"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."
"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."
"The most valuable feature is the S/4HANA 1909 On-Premise"
"Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."
"Documentation needs to be improved"
"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."
"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."
"Lacks integrations with AWS, GCP and the like."
"We can't scale it to meet digital requirements."
"Sometimes, Windows-related functions do not work properly in Denodo. The analytic functions in SQL do not work properly."
"Denodo currently integrates with ChatGPT, but the ability to manage and utilize them directly within Denodo would be a significant improvement."
"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."
"The company has everything offshore."
"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."
Denodo is ranked 1st in Data Virtualization with 29 reviews while SAP Data Hub is ranked 25th in Data Governance with 3 reviews. Denodo is rated 7.8, while SAP Data Hub is rated 7.6. 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 SAP Data Hub writes "The solution is seamless, but the database sometimes leads to confusion". Denodo is most compared with Azure Data Factory, AWS Glue, Delphix, Mule Anypoint Platform and Informatica PowerCenter, whereas SAP Data Hub is most compared with Microsoft Purview, SAP Data Services, Alation Data Catalog, Azure Data Factory and Palantir Foundry.
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