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Azure Data Factory vs Qlik Compose 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:
 

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)
Qlik Compose
Ranking in Data Integration
34th
Average Rating
7.6
Reviews Sentiment
6.5
Number of Reviews
12
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2025, in the Data Integration category, the mindshare of Azure Data Factory is 7.4%, down from 11.9% compared to the previous year. The mindshare of Qlik Compose is 1.2%, up from 0.9% 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.
Sahil Taneja - PeerSpot reviewer
Easy matching and reconciliation of data
The initial setup was easy for the data warehousing concept. But for a person who is new to ETL and warehousing concepts, it may take some time. If someone is familiar with these concepts, they could understand and learn the tool quickly. However, compared to other tools, the UI is complex. It would be helpful to have a better UI and documentation for new users. As of now, there is a challenge in learning the Compose tool for new users altogether. Qlik Compose was deployed on-premises. But the servers, like the SQL servers were maintained on the cloud—the managed instances.

Quotes from Members

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

Pros

"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"Azure Data Factory is a low code, no code platform, which is helpful."
"I am one hundred percent happy with the stability."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."
"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."
"We haven't had any issues connecting it to other products."
"We have found the bulk load feature very valuable."
"It's a stable solution."
"It is a scalable solution."
"I like modeling and code generation. It has become a pretty handy tool because of its short ideation to delivery time. From the time you decide you are modeling a data warehouse, and once you finish the modeling, it generates all the code, generates all the tables. All you have to do is tick a few things, and you can produce a fully functional warehouse. I also like that they have added all the features I have asked for over four years."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"I have found it to be a very good, stable, and strong product."
"As long as you pick the solution that best fits with your requirements, you won't find that performance is a problem. It's good."
"It can scale."
"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."
 

Cons

"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"There is a problem with the integration with third-party solutions, particularly with SAP."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"Data Factory's monitorability could be better."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"The solution has room for improvement in the ETL. They have an ETL, but when it comes to the monitoring portion, Qlik Compose doesn't provide a feature for monitoring."
"When processing data from certain tables with a large volume of data, we encounter significant delays. For instance, when dealing with around one million records, it typically takes three to four hours. To address this, I aim to implement performance improvements across all tables, ensuring swift processing similar to those that are currently complete within seconds. The performance issue primarily arises when we analyze the inserts and updates from the source, subsequently dropping the table. While new insertions are handled promptly, updates are processed slowly, leading to performance issues. Despite consulting our Qlik vendors, they were unable to pinpoint the exact cause of this occurrence. Consequently, I am seeking ways to optimize performance within Qlik Compose, specifically concerning updates."
"It could enhance its capabilities in the realm of self-service options as currently, it is more suited for individuals with technical proficiency who can create pages using it."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"Qlik's ETL and data transformation could be better."
"There could be more customization options."
"There should be proper documentation available for the implementation process."
"My issues with the solution's stability are owing to the fact that it has certain bugs causing issues in some functionalities that should be working."
 

Pricing and Cost Advice

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"Understanding the pricing model for Data Factory is quite complex."
"The pricing is a bit on the higher end."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"The cost is based on the amount of data sets that we are ingesting."
"I don't see a cost; it appears to be included in general support."
"The pricing model is based on usage and is not cheap."
"I would not say that this product is overly expensive."
"While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us."
"The price of the solution is expensive."
"On a scale of one to ten, where one is cheap, and ten is very expensive, I rate the solution a six."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
Financial Services Firm
15%
Manufacturing Company
10%
Government
9%
Computer Software Company
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...
Which ETL tool would you recommend to populate data from OLTP to OLAP?
There are two products I know about * TimeXtender : Microsoft based, Transformation logic is quiet good and can easily be extended with T-SQL , Has a semantic layer that generates metat data for cu...
What do you like most about Qlik Compose?
The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities.
What is your experience regarding pricing and costs for Qlik Compose?
While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us.
 

Also Known As

No data available
Compose, Attunity Compose
 

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
Poly-Wood
Find out what your peers are saying about Azure Data Factory vs. Qlik Compose and other solutions. Updated: July 2025.
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