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."One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."
"The solution is okay."
"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"Allows more data between on-premises and cloud solutions"
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
"It is easy to virtualize data using the solution."
"It allows a lot of traceability and you can decide what data you want to collect"
"Access to numerous forums and internet information."
"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."
"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 ability to transfer data is very valuable."
"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."
"The most valuable features are data lineage and the concept of a semantic layer."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"We require Azure Data Factory to be able to connect to Google Analytics."
"Currently, smaller businesses face a disadvantage in terms of pricing, and reducing costs could address this issue."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"The setup and configuration process could be simplified."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"Lacks in-built streaming data processing."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"We occasionally have some integration issues that we need to work through."
"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."
"Denodo has some difficulty supporting large numbers of records."
"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 dropdown menus feel antiquated to me, and the administrative portals need improvement."
"It would be good if the solution provided a much-needed cellular platform."
"The integration could use improvement, it's a lot of non-speed line processes that we have discovered, in the country. The configurations could use a lot more improvement."
"The git configuration really should be improved."
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.