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Azure Data Factory vs Denodo comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
86
Ranking in other categories
Cloud Data Warehouse (3rd)
Denodo
Ranking in Data Integration
14th
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
34
Ranking in other categories
Data Virtualization (1st), Cloud Data Integration (11th)
 

Mindshare comparison

As of December 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.0%, down from 13.3% compared to the previous year. The mindshare of Denodo is 1.9%, down from 2.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Thulani David Mngadi - PeerSpot reviewer
Data flow feature is valuable for data transformation tasks
The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.
Dash Bibhuprasad - PeerSpot reviewer
Saves our underwriters' time with data virtualization, but could provide more learning resources
As a company, we first did a proof-of-concept for about four months to make sure the product was a perfect fit for us or not, and beyond that I have only used Denodo for another year or so, so I know that we haven't used the product to its fullest yet. Indeed, a lot of Denodo has changed since we had our first presentation on it with the Denodo sales team who gave us a rundown of all the features. Nevertheless, there are multiple ideas I could suggest in terms of improvement. First of all, the visualization and reporting could be better. Of course, the data virtualization is good, but the data visualization could be improved with regards to the real-time dashboarding of the graphs, pie charts, etc. For the real-time data, the dashboard should preferably be updated automatically every hour. Let's say, as a CEO or CFO, I just want to know how much premium the company will get at any hour of the day. This data should be readily available on the dashboard. This is largely why we stick with Power BI's dashboarding features (besides the simple fact that Power BI works well hand-in-hand with Azure), and why we still haven't used Denodo's data visualization features as much as the data virtualization features. Another area we have been struggling with is the integration of Denodo with both Salesforce and MuleSoft, which we use to track the customers in our sales system, such as when sending insurance quotes. When we first tried to integrate Salesforce, we found that there was some type of version incompatibility. We had a hard time talking with Salesforce about this, but eventually we upgraded our version and the integration was resolved. Yet, this was a challenge that I feel we didn't need to go through, as we were not able to quickly map out the issue. And with MuleSoft, we have not been able to integrate it properly at all. I have also seen our users complain about the availability of data sources, where they are sometimes not able to connect to all the sources they need. This kind of complaint, however, is difficult to diagnose, and I don't know for sure whether it is due to how we have Denodo set up in the company, or whether it's an actual issue with Denodo itself. These complaints were mainly made during the first few months of our usage, so it is possible that the problems stemmed from a lack of knowledge on how to use Denodo correctly, especially since the individual feedback would generally be something vague like, "Okay, I'm not able to do this". To help resolve these complaints, I would suggest that Denodo work on better documentation and perhaps some kind of virtual training. For example, there's an insurance software company called Guidewire, and when we first brought Guidewire into the company they sent us a lot of training videos even before the actual integration took place. For Denodo, it would be beneficial to make sure that the team that will be using it 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. They say, "You are pushing us too hard", so they need encouragement when it comes to adoption of a new software product.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
"The data copy template is a valuable feature."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"The most valuable feature is the copy activity."
"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"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."
"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 feature of Denodo is its uniformity of self-site data access types, which allows it to connect to almost any storage technology and feed it transparently."
"The data abstraction is the most valuable feature."
"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)."
"Denodo's best features are its performance, easy data transformation, and the job scheduler."
"Denodo provides several server connectivity options with other tools such as ODPC and UDPC. It supports API integrations, allowing integration with a wide range of databases using different technologies, including NoSQL and relational databases."
"The ability to transfer data is very valuable."
 

Cons

"When we initiated the cluster, it took some time to start the process."
"The support and the documentation can be improved."
"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"Lacks in-built streaming data processing."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"The product integration with advanced coding options could cater to users needing more customization."
"There is no built-in pipeline exit activity when encountering an error."
"We would like this solution to be more universally user-friendly. At present it is really only aimed at IT specialists."
"Tasks such as conversion of a date format or conversion of a number format that can be done in a very easy way in different languages, like SQL or Oracle, are not so easy to do in Denodo. For example, if you want to convert a date from one format to another, in Oracle it's pretty easy; in Denodo, however, it requires so many lines of code. Simple things that can be done very quickly in other database languages require more lines of code in Denodo."
"The support is not the best and should be improved."
"We can't scale it to meet digital requirements."
"The dropdown menus feel antiquated to me, and the administrative portals need improvement."
"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."
"Data transformation must be improved."
"I am still waiting for Denodo to support vector databases."
 

Pricing and Cost Advice

"The price is fair."
"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"This is a cost-effective solution."
"I would not say that this product is overly expensive."
"I would rate Data Factory's pricing nine out of ten."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"Data Factory is expensive."
"I am not super familiar with the pricing, but so far, it seems good. We have been happy. We haven't seen any problems. The only time we had to pay extra was during the upgrade. We didn't upgrade at the time they told us to upgrade, and we had to pay extra to keep the service. They had stopped the support for the older version and moved to the newer version. It was not their fault. It was our fault because we didn't get on board quickly."
"Cost wise, on a scale from one to five, with one being the cheapest and five being the most expensive, Denodo would be at three. We get all the features in a bundle."
"There is an express edition and a licensed enterprise edition."
"For us, the cost has been okay. Also, there are no additional costs; it's just the standard licensing fee."
"The pricing is pretty good, and I would rate it at four out of five."
"The cost for Denodo is in line with other similar products."
"Denodo provides a lightweight 30-day free trial, but when we do courses on top of it, it costs $150 for each person."
"The licensing should be improved, as the cost per connector is quite expensive."
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Answers from the Community

SO
Dec 2, 2021
Dec 2, 2021
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 ano...
2 out of 3 answers
EB
Nov 16, 2021
Hi @Rushabh-Shah, @Kevin Monte De Ramos, @Avi Shvartz ​and @AmitJain. Can you please assist here and share your knowledge with the community?
DG
Nov 18, 2021
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.
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
21%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
Does Denodo provide useful data virtualization education? Is it useful to attend their training?
If you are a Denodo user, it makes sense to undergo their training. Different types of professionals can benefit from it, including administrators, developers, and architects. If you are keen on i...
In experience, what might Denodo be lacking or need improvement on?
I like Denodo a lot. It offers quick and easy web service deployment within minutes. There are not any flaws that I think make the product less good or effective. The only thing I can point out is...
Which industries can benefit from Denodo the most?
Denodo is suitable for pretty much all sectors that deal with: Big data Cloud solutions Data governance Logical data fabric Master data management In my opinion, organizations in different fields...
 

Learn More

 

Overview

 

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
Autodesk, VHA, AAA, Sumitomo Mitsui Trust Bank, Caterpillar, European Chemical Agency, Seagate, Nationwide, Time Warner Cable, Pantex, Inditex, BNSF Railways, Vodafone, CIT Group, Jazztel, Wolters Kluwer, Telefonica, TransAlta
Find out what your peers are saying about Azure Data Factory vs. Denodo and other solutions. Updated: December 2024.
824,053 professionals have used our research since 2012.