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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
6.9
Number of Reviews
90
Ranking in other categories
Cloud Data Warehouse (3rd)
Qlik Compose
Ranking in Data Integration
24th
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 2025, in the Data Integration category, the mindshare of Azure Data Factory is 10.1%, down from 12.9% compared to the previous year. The mindshare of Qlik Compose is 1.1%, 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

"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"In terms of my personal experience, it works fine."
"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."
"The solution is okay."
"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."
"We haven't had any issues connecting it to other products."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"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."
"It can scale."
"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."
"I have found it to be a very good, stable, and strong product."
"It is a scalable solution."
"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."
"The technical support is very good. I rate the technical support a ten out of ten."
 

Cons

"My only problem is the seamless connectivity with various other databases, for example, SAP."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"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 in-built streaming data processing."
"The product integration with advanced coding options could cater to users needing more customization."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."
"There could be more customization options."
"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."
"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."
"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."
"There should be proper documentation available for the implementation process."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"I'd like to have access to more developer training materials."
 

Pricing and Cost Advice

"Understanding the pricing model for Data Factory is quite complex."
"The cost is based on the amount of data sets that we are ingesting."
"The pricing model is based on usage and is not cheap."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"I don't see a cost; it appears to be included in general support."
"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."
"The price of the solution is expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
16%
Government
11%
Computer Software Company
9%
Manufacturing Company
9%
 

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: January 2025.
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