Try our new research platform with insights from 80,000+ expert users

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
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (2nd)
Qlik Compose
Ranking in Data Integration
46th
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 February 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.0%, down from 9.8% compared to the previous year. The mindshare of Qlik Compose is 0.9%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.0%
Qlik Compose0.9%
Other96.1%
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.
Sahil Taneja - PeerSpot reviewer
Principal Consultant/Manager at Tenzing
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

"An excellent tool for pipeline orchestration."
"The function of the solution is great."
"From what we have seen so far, the solution seems very stable."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
"I like the basic features like the data-based pipelines."
"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."
"It's a stable 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 most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."
"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."
"I have found it to be a very good, stable, and strong product."
"It can scale."
"The technical support is very good. I rate the technical support a ten out of ten."
"There were many valuable features, such as extracting any data to put in the cloud. For example, Qlik was able to gather data from SAP and extract SAP data from the platforms."
 

Cons

"Data Factory's performance during heavy data processing isn't great."
"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"The setup and configuration process could be simplified."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"We require Azure Data Factory to be able to connect to Google Analytics."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"Azure Data Factory's pricing in terms of utilization could be improved."
"Qlik's ETL and data transformation could be better."
"For more complex work, we are not using Qlik Compose because it cannot handle very high volumes at the moment. It needs the same batching capabilities that other ETL tools have. We can't batch the data into small chunks when transforming large amounts of data. It tries to do everything in one shot and that's where it fails."
"There could be more customization options."
"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."
"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."
"I believe that visual data flow management and the transformation function should be improved."
"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'd like to have access to more developer training materials."
 

Pricing and Cost Advice

"The solution's pricing is competitive."
"Product is priced at the market standard."
"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."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"ADF is cheaper compared to AWS."
"I don't see a cost; it appears to be included in general support."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"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."
"While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
882,813 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Financial Services Firm
14%
Government
12%
Manufacturing Company
10%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise57
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: February 2026.
882,813 professionals have used our research since 2012.