We performed a comparison between Azure Data Factory and Denodo 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 function of the solution is great."
"It is a complete ETL Solution."
"The most important feature is that it can help you do the multi-threading concepts."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"From what we have seen so far, the solution seems very stable."
"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."
"Data Factory's best features are simplicity and flexibility."
"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."
"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."
"It is easy to virtualize data using the solution."
"The most valuable feature is Data Catalogs."
"In general, it's good for us to make tests so we can scout the data."
"The most valuable features are query optimization and the single language independence from the sources we're using to catch data."
"The best thing about Denodo is that creating and deploying a web service can be done in about 10 minutes, compared to a whole day when it comes to other solutions (such as when deploying with Java and AWS)."
"The most valuable aspects of this solution are the short time frame in which you can deliver and connect."
"There's space for improvement in the development process of the data pipelines."
"Some known bugs and issues with Azure Data Factory could be rectified."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"The pricing scheme is very complex and difficult to understand."
"The speed and performance need to be improved."
"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."
"When the record fails, it's tough to identify and log."
"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."
"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."
"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."
"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."
"We can't scale it to meet digital requirements."
"There are a couple of areas that can be improved in Denodo. From a stability point of view, sometimes we see issues in the data management functionality. This only happens now and then, however, and usually takes place when we add in our own customization."
"It would be beneficial to make sure that the team that will be using Denodo has some kind of training on how to use the product at least a month beforehand, and there could even be some kind of feedback or Q&A sessions to go along with the training. If Denodo were able to provide this kind of training, it would be very helpful to users in insurance and banking companies because the staff are typically older and not always technically-minded."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Denodo is ranked 12th in Data Integration with 29 reviews. Azure Data Factory is rated 8.0, while Denodo is rated 7.8. 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 Denodo writes "Saves our underwriters' time with data virtualization, but could provide more learning resources". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Oracle GoldenGate, whereas Denodo is most compared with AWS Glue, Delphix, Mule Anypoint Platform, Informatica PowerCenter and Palantir Foundry. See our Azure Data Factory vs. Denodo report.
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Greetings, Stefan.
Alteryx is basically an ETL tool that evolved to deliver some Data Viz and ML features too. This means that its main purpose is to extract data from different sources, combine and transform them and finally load them in a different database.
Denodo is a data virtualization tool, which means it does all the transformations without extracting from one place and loading to another one. It´s a cloud-based solution and it charges by the traffic. If your company has specific General Data Protection Regulation that prohibits for instance that you extract the data located in a data center in Europe and loading them in a cluster located in the USA, you will probably need a virtualization tool like Denodo instead of an ETL like Alteryx. Virtualization tools are usually more expensive in a long run
Azure Data Factory is a platform meant to leverage the use of Azure. Microsoft´s objective is to sell its cloud solution as a whole. It contains a Data Studio (to manage and control your data), SPARK (which is a Hadoop in memory) and a data lake storage.
As you see, those are 3 different products that do not make much sense to be used together.
I'd say that there is a misconception in some of the answers (but don't worry, it's a common one).
Alteryx is not an ETL tool, it's an analytics platform with very powerful ETL capabilities (accessing mostly all data sources available and processing them at high speeds among others).
But additionally, Alteryx gives you the ability to carry on with the complete analytics cycle, processing, cleaning, blending those diverse data sources, modeling descriptive, predictive, prescriptive analytics (plus some ML & AI), outputting to another humongous variety of data sources, reporting or visualization tools.
All of the previous can be achieved with no coding at all, but in case you want to code, Alteryx also offers Python, R & Scala native integration. In other words, it can solve business users' use cases and advanced/technical use cases at the same time.
Finally, it's a fixed license, with no additional costs per usage (at least so far, until they release the Cloud Version).
I hope I was able to clarify the role of Alteryx in the analytics landscape.