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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
4th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
Ranking in other categories
Cloud Data Warehouse (5th)
Qlik Compose
Ranking in Data Integration
49th
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 June 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 8.1% compared to the previous year. The mindshare of Qlik Compose is 0.8%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.3%
Qlik Compose0.8%
Other96.9%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
SA
Director - Metrics & Analytics at a computer software company with 1,001-5,000 employees
Efficient data warehouse automation with robust features, but may require enhancements in user-friendly self-service options and pricing flexibility for broader corporate appeal
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. When it comes to end users who may lack technical expertise, they are limited to toggling between existing developments. To empower end users to make critical changes without relying heavily on technical expertise, it would be beneficial to introduce more user-friendly features for development and modification. If it could incorporate correlation analysis capabilities into its platform, especially in a user-friendly manner, it would greatly enhance the tool's overall utility and make it an even more outstanding solution. There is a room for improvement regarding stability.

Quotes from Members

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

Pros

"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"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."
"We have used other ETL solutions in the past, and Azure Data Factory is the best one."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."
"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."
"It can scale."
"It is a scalable solution."
"One of the most valuable features of this tool is its automation capabilities, allowing us to design the warehouse in an automated manner. Additionally, we can generate Data Lifecycle Policies (DLP) reports and efficiently implement updates and best practices based on proven design patterns."
"The technical support is very good. I rate the technical support a ten out of ten."
"Qlik Compose is good enough; it is user-friendly and intuitive."
"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"I have found it to be a very good, stable, and strong product."
 

Cons

"It would be better if it had machine learning capabilities."
"It can improve from the perspective of active logging. It can provide active logging information."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"It can improve from the perspective of active logging."
"The number of standard adaptors could be extended further."
"There is no built-in pipeline exit activity when encountering an error."
"There could be more customization options."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"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."
"I don't think Qlik can be used in a high-volume scenario. It didn't work for us."
"I believe that visual data flow management and the transformation function should be improved."
"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."
"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."
"It would be better if the first level of technical support were a bit more technically knowledgeable to solve the problem. I think they could also improve the injection of custom scripts. It is pretty difficult to add additional scripts. If the modeling doesn't give you what you want, and you want to change the script generated by the modeling, it is a bit more challenging than in most other products. It is very good with standard form type systems, but if you get a more complicated data paradigm, it tends to struggle with transforming that into a model."
 

Pricing and Cost Advice

"The pricing is a bit on the higher end."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"I would rate Data Factory's pricing nine out of ten."
"The solution is cheap."
"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."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"Data Factory is affordable."
"Understanding the pricing model for Data Factory is quite complex."
"The price of the solution is expensive."
"While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us."
"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
12%
Computer Software Company
10%
Manufacturing Company
9%
Government
6%
Financial Services Firm
12%
Government
11%
Manufacturing Company
9%
Comms Service Provider
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise3
Large Enterprise6
 

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...
 

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: April 2026.
896,563 professionals have used our research since 2012.