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Azure Data Factory vs Denodo comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

Review summaries and opinions

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

ROI

Sentiment score
7.3
Azure Data Factory enhances efficiency, centralizes data, reduces costs, and improves data analysis, offering significant financial and operational benefits.
Sentiment score
6.8
Denodo improved efficiency, ROI, decision-making, reduced churn, and increased loyalty, significantly enhancing data processing and systems replacement.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
 

Customer Service

Sentiment score
6.5
Azure Data Factory support is responsive but varies in speed, with community resources and documentation aiding user satisfaction.
Sentiment score
7.2
Denodo's support is praised for responsiveness and expertise but criticized for slow bug fixes and lack of proactive engagement.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
The technical support for Azure Data Factory is generally acceptable.
They have a good methodology for learning how to use the tool.
Denodo's customer support team is very competent and responsive.
If we raise a ticket, it can be resolved or addressed within a reasonable time frame, so support is good.
 

Scalability Issues

Sentiment score
7.5
Azure Data Factory excels in scalability, efficiently managing workloads for any size, despite higher costs than alternatives.
Sentiment score
7.5
Denodo is scalable and integrates widely but may require additional management for performance and cost efficiency.
Azure Data Factory is highly scalable.
For huge data requests, it cannot scale automatically; admin action is required.
While the solution scales well on a single machine, I have doubts about its scalability when deployed as part of a Java component cluster.
Its complexity in configuring and the requirement to install different connectors for different sources affects its scalability.
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is stable and reliable, but faces integration challenges and requires enhancements to compete with top competitors.
Sentiment score
6.9
Denodo offers robust stability with minor bugs; high reliability improves in the latest version despite complex scenario challenges.
The solution has a high level of stability, roughly a nine out of ten.
I would rate it nine out of ten because it is very reliable, always performing as expected.
If JVM does not function properly, it may cause Denodo to fail to connect to different sources.
 

Room For Improvement

Azure Data Factory needs improved integration, better scheduling, enhanced UI, simplified pricing, more connectors, and responsive support.
The system needs comprehensive improvements in functionality, integration, support, UI, scalability, security, documentation, and external tool compatibility.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
There is a problem with the integration with third-party solutions, particularly with SAP.
Ensuring data caching is up to date is critical.
Denodo needs better communication on how the product can be deployed for specific solutions.
The system has dependencies on other environments, like JVM, which can affect its performance.
 

Setup Cost

Azure Data Factory pricing is usage-based and cost-effective, but large data volumes can lead to increased expenses.
Denodo pricing is costly, designed for large enterprises, with complex licensing and costs varying by customer needs.
The pricing is cost-effective.
It is considered cost-effective.
Denodo is considered pricey, limiting its use to large enterprises or government organizations that can afford its comprehensive setup.
Denodo's pricing is not affordable for small companies and is more suitable for medium to large enterprises.
 

Valuable Features

Azure Data Factory provides seamless data integration, robust transformations, scalability, and strong SAP support, praised for its ease of use.
Denodo is praised for data virtualization, efficiently integrating and managing diverse sources with strong security, introspection, and visualization.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with.
Denodo's ability to connect to multiple data sources and perform extract-transform-load (ETL) operations on the fly is noteworthy.
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.
Denodo supports SQL base, so if you want to join two tables or two views, you can use SQL, which is an advantage as most developers or business people know SQL.
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Cloud Data Warehouse (2nd)
Denodo
Ranking in Data Integration
13th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
37
Ranking in other categories
Data Virtualization (1st), Cloud Data Integration (10th)
 

Mindshare comparison

As of June 2025, in the Data Integration category, the mindshare of Azure Data Factory is 8.4%, down from 12.3% compared to the previous year. The mindshare of Denodo is 1.9%, down from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
Atanu Chatterjee - PeerSpot reviewer
Data virtualization and integration enabled while caching and scalability room for improvement
In terms of improvements for Denodo, regarding performance, in cases where there are multiple virtualizations—such as reading from one Denodo view that is virtualized, and from that view there's also virtualization, and another team is reading from that view—if multiple virtualizations happen with no caching in between, it becomes slow. This occurs because it is cascading; whenever at the top level someone is reading data, that request is getting cascaded to the nth level, causing issues, especially in cases such as Power BI reports. We need to consider implementing some persistent layer in between. The scaling process should improve because many things are getting automated. The scale-out part needs to be automated, though I am uncertain whether Denodo has already implemented that feature.
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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
14%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
22%
Manufacturing Company
10%
Computer Software Company
9%
Government
7%
 

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...
 

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: June 2025.
859,579 professionals have used our research since 2012.