Azure Data Factory vs Qlik Compose comparison

Why PeerSpot?

Microsoft and Qlik are both solutions in the Data Integration category. Microsoft is ranked #6 with an average rating of 8.0, while Qlik is ranked #57. Microsoft holds a 2.2% mindshare in DI, compared to Qlik’s 0.8% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 81% of Qlik users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

15,321 Views
10,725 Comparison Views

92% willing to recommend

Qlik Compose

Read 12 Qlik Compose reviews

2,980 Views
2,354 Comparison Views

81% willing to recommend

Azure Data Factory

Qlik Compose

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

Qlik Compose and Azure Data Factory are both powerful tools in the category of data integration and transformation. Despite Qlik Compose's appealing pricing and support, Azure Data Factory often emerges as the preferred choice due to its robust features and superior scalability.

Features: Qlik Compose offers data warehouse automation, change data capture, and lifecycle management, enabling accelerated deployment of analytics-ready data. Azure Data Factory shines with its extensive data orchestration and transformation tools, seamless integration with various cloud services, and over 100 out-of-the-box connectors supporting diverse data sources. It is also recognized for its flexibility and the ability to handle complex data flows, making it ideal for large-scale enterprise applications.

Room for Improvement: Qlik Compose could enhance its real-time processing capabilities and expand its cloud integration options to better compete with Azure's flexibility. Additionally, improved scalability features could help it cater to more extensive and complex deployments. On the other hand, Azure Data Factory users desire improvements in interface speed and more advanced monitoring features. Some users also find that its pricing model can become costly, possibly limiting its appeal for smaller companies with budget constraints.

Ease of Deployment and Customer Service: Qlik Compose's deployment is user-friendly with a focus on model-driven pipelines, beneficial for teams with limited technical expertise. It is also noted for its reliable support system. Azure Data Factory, offering detailed documentation and community support, suits intricate deployments across diverse environments. While its setup may be complex, these resources aid in troubleshooting and ensure a smooth deployment process.

Pricing and ROI: Qlik Compose is praised for its straightforward and cost-effective pricing, aligning with its automated functionality. Azure Data Factory, though perceived as more expensive due to its extensive capabilities, is considered worth the investment for those needing advanced and scalable solutions, offering significant ROI for enterprises with comprehensive data strategy requirements.

To learn more, read our detailed Azure Data Factory vs. Qlik Compose Report (Updated: September 2026).

Buyer's Guide

Azure Data Factory vs. Qlik Compose

September 2026

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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

6th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (6th)

Qlik Compose

Ranking in Data Integration

57th

Average Rating

7.6

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 5.1% compared to the previous year. The mindshare of Qlik Compose is 0.8%, down from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.2%
Qlik Compose	0.8%
Other	97.0%

Data Integration

Featured Reviews

Kunal Das

Test Engineer at Happiest Minds Technologies

Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling

If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.

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Susheel A

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.

Read full review

Quotes from Members

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

Pros

"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

"The data pipeline and the orchestration functionality are the most valuable aspects of the solution, and the interface is very good, as it seeks to be very responsive and intuitive."

"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."

"The overall architecture has been very valuable to us, as it has allowed us to scale up pretty rapidly."

"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."

"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."

"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."

More Azure Data Factory pros

"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."

"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."

"I have found it to be a very good, stable, and strong product."

"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."

"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."

"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."

"It is a scalable solution."

More Qlik Compose pros

Cons

"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."

"There are performance issues, particularly with the underlying compute, which should be configurable."

"Lacks a decent UI that would give us a view of the kinds of requests that come in."

"The number of standard adaptors could be extended further."

"Azure Data Factory is a bit complicated compared to Informatica. There are a lot of connectors that are missing and there are a lot of instances where I need to create a server and install Integration Runtime."

"DataStage is easier to learn than Data Factory because it's more visual."

"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."

"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."

More Azure Data Factory cons

"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."

"Qlik's ETL and data transformation could be better."

"There is some scope for improvement around the documentation, and a better UI would definitely help."

"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."

"I'd like to have access to more developer training materials."

"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."

More Qlik Compose cons

Pricing and Cost Advice

"The solution's pricing is competitive."

"It's not particularly expensive."

"I would rate Data Factory's pricing nine out of ten."

"The licensing is a pay-as-you-go model, where you pay for what you consume."

"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."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

"The licensing cost is included in the Synapse."

More Azure Data Factory pricing and cost advice

"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

11%

Manufacturing Company

Computer Software Company

Outsourcing Company

Financial Services Firm

12%

Comms Service Provider

10%

Construction Company

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	3
Large Enterprise	6

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.

See all answers

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...

See all answers

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...

See all answers

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...

See all answers

Comparisons

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

AWS Database Migration Service vs Qlik Compose

Compared 8% of the time

Qlik Replicate vs Qlik Compose

Compared 8% of the time

SSIS vs Qlik Compose

Compared 7% of the time

Qlik Talend Cloud vs Qlik Compose

Compared 5% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Qlik Compose

Compared 5% of the time

More Qlik Compose Competitors

Product Reports

Buyer's Guide

Azure Data Factory

October 2026

Download Azure Data Factory product report

Buyer's Guide

Qlik Compose

October 2026

Download Qlik Compose product report

Also Known As

No data available

Compose, Attunity Compose

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

Qlik Compose enhances data management with ETL capabilities, data integration with CDC, and real-time replication. Its intuitive interface enables easy data modeling and automation, supporting various database integrations.

Qlik Compose is designed for efficient data preparation, migration, and warehouse generation. It incorporates ETL functionalities and data integration with CDC, allowing users to effortlessly create data marts without code. Its automation features facilitate warehouse design while graphical representations and connectivity options increase versatility across multiple sources. Users value its stability, scalability, and the support provided, although improvements in ETL functionalities, performance for large datasets, and NoSQL integration are needed. The solution is widely used in business intelligence with tools like Qlik Replicate for real-time data replication and requires direct SQL for complex transformations.

What are the key features of Qlik Compose?

ETL Capabilities: Simplifies data extraction, transformation, and loading
Data Integration with CDC: Enables real-time data replication
Intuitive Interface: Facilitates easy data modeling and automation
Drag-and-Drop Functionality: Streamlines data task management
Auto-Mapping: Enhances integration of multiple data sources
No-Code Data Marts Creation: Reduces dependency on technical skills

What benefits should users consider in the reviews?

Stability and Scalability: Reliable functioning for growing data needs
Technical Support: Availability of assistance for troubleshooting
Real-Time Replication Capabilities: Efficient data processing and analytics
Low-Code Development: Simplifies complex data handling processes

In industries, Qlik Compose is implemented for enhancing data preparation, migration, and warehousing. It is used in small projects or straightforward data integration tasks and supports business intelligence efforts by offering low-code capabilities, enabling companies to deliver tailored analytics solutions efficiently.

Qlik

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

Buyer's Guide

Azure Data Factory vs. Qlik Compose

September 2026

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