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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
7.1
Azure Data Factory automates data processes, cuts costs, and improves efficiency, offering potential ROI of 20%-30% over five years.
Sentiment score
8.0
Denodo enhances ROI by speeding processes, improving strategic accuracy, reducing churn, and boosting customer loyalty within six months.
 

Customer Service

Sentiment score
6.5
Azure Data Factory support is responsive and helpful, though response times and efficiency vary based on issue complexity and support package.
Sentiment score
7.2
Denodo's service and support are praised for expertise and promptness, but initial support and training need improvement.
The technical support is responsive and helpful
The technical support from Microsoft is rated an eight out of ten.
The documentation is very thorough.
Denodo's customer support team is very competent and responsive.
They are proactive in conducting webinars and connecting with customers.
 

Scalability Issues

Sentiment score
7.5
Azure Data Factory is scalable and flexible for enterprises, though some concerns about costs and external integration exist.
Sentiment score
7.6
Denodo offers scalable architecture with successful integration and deployment, overcoming financial and query delegation challenges to ensure performance.
Azure Data Factory is highly scalable.
Its complexity in configuring and the requirement to install different connectors for different sources affects its scalability.
While the solution scales well on a single machine, I have doubts about its scalability when deployed as part of a Java component cluster.
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is reliable, scoring 8-9/10, though some report occasional glitches or slowdowns under heavy loads.
Sentiment score
7.1
Denodo is stable, handles stress well, but faces occasional challenges with complex queries and external dependencies.
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 better integration, simplified UI, improved connectivity, enhanced support, clearer pricing, and performance scalability for large data.
Denodo requires improvements in data catalog, integration, modernization, connectivity, security, performance, visualization, documentation, and user-friendliness.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
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 has complex pricing, with costs varying widely due to usage, data volume, and additional services.
Denodo's pricing is expensive but fair for enterprises, with various editions and licensing often based on CPU or core.
The pricing is cost-effective.
It is considered cost-effective.
Denodo's pricing is not affordable for small companies and is more suitable for medium to large enterprises.
Denodo is considered pricey, limiting its use to large enterprises or government organizations that can afford its comprehensive setup.
 

Valuable Features

Azure Data Factory provides scalable data transformation, integration, and orchestration with user-friendly interface and extensive connector support.
Denodo offers efficient data virtualization with robust integration, optimized queries, and secure access, enhancing analytics and data management.
It connects to different sources out-of-the-box, making integration much easier.
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 is also effective for developing solutions quickly, facilitating user reports, and offering good data governance.
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
89
Ranking in other categories
Cloud Data Warehouse (3rd)
Denodo
Ranking in Data Integration
10th
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
36
Ranking in other categories
Data Virtualization (1st), Cloud Data Integration (6th)
 

Mindshare comparison

As of January 2025, in the Data Integration category, the mindshare of Azure Data Factory is 10.8%, down from 13.4% 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

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.
Vishal_Goyal - PeerSpot reviewer
The data catalog feature helps define data structures without storing data
The data catalog feature is valuable as it helps define data structures without storing data. Denodo's ability to connect to multiple data sources and perform extract-transform-load (ETL) operations on the fly is noteworthy. It supports API usage to call and present data in JSON or Tableau format without visualization capabilities.
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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...
 

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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: January 2025.
831,158 professionals have used our research since 2012.