Azure Data Factory vs Qlik Compose comparison

Microsoft and Qlik are both solutions in the Data Integration category. Microsoft is ranked #3 with an average rating of 8.2, while Qlik is ranked #48. Microsoft holds a 2.8% mindshare in DI, compared to Qlik’s 1.0% 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 94 Azure Data Factory reviews

10,752 Views
7,526 Comparison Views

92% willing to recommend

Qlik Compose

Read 12 Qlik Compose reviews

1,724 Views
1,500 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: March 2026).

Buyer's Guide

Azure Data Factory vs. Qlik Compose

March 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

3rd

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (2nd)

Qlik Compose

Ranking in Data Integration

48th

Average Rating

7.6

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.8%, down from 9.7% compared to the previous year. The mindshare of Qlik Compose is 1.0%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.8%
Qlik Compose	1.0%
Other	96.2%

Data Integration

Featured Reviews

KandaswamyMuthukrishnan

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.

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Sahil Taneja

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.

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Quotes from Members

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

Pros

"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."

"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."

"The solution can scale very easily."

"In terms of my personal experience, it works fine."

"The solution handles large volumes of data very well. One of its best features is its ability to integrate data end-to-end, from pulling data from the source to accessing Databricks. This makes it quite useful for our needs."

"It is easy to integrate."

"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."

"In terms of my personal experience, it works fine."

More Azure Data Factory pros

"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."

"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."

"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."

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

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

"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."

More Qlik Compose pros

Cons

"In the next release, it's important that some sort of scheduler for running tasks is added."

"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."

"The one element of the solution that we have used and could be improved is the user interface."

"Some known bugs and issues with Azure Data Factory could be rectified."

"To my mind, the solution needs to be more connectable to its own services."

"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."

"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."

"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."

More Azure Data Factory cons

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

"There should be proper documentation available for the implementation process."

"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."

"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."

"I believe that visual data flow management and the transformation function should be improved."

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

More Qlik Compose cons

Pricing and Cost Advice

"It's not particularly expensive."

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

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

"The pricing model is based on usage and is not cheap."

"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"The licensing cost is included in the Synapse."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

More Azure Data Factory pricing and cost advice

"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

12%

Computer Software Company

10%

Manufacturing Company

Government

Financial Services Firm

11%

Construction Company

11%

Government

11%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	20
Large Enterprise	57

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 5% of the time

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

Compared 5% of the time

Palantir Foundry vs Azure Data Factory

Compared 4% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

Informatica PowerCenter vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Qlik Replicate vs Qlik Compose

Compared 12% of the time

Qlik Talend Cloud vs Qlik Compose

Compared 10% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Qlik Compose

Compared 9% of the time

WhereScape RED vs Qlik Compose

Compared 6% of the time

Airbyte Cloud vs Qlik Compose

Compared 6% of the time

More Qlik Compose Competitors

Product Reports

Buyer's Guide

Azure Data Factory

March 2026

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Buyer's Guide

Qlik Compose

March 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 Sense is a powerful business intelligence tool that offers a range of features to help organizations make faster and more informed decisions. Its primary use cases include operational and financial dashboards, self-service reporting, and centralized access to cross-functional reports. The solution is praised for its mobile platform, ease of use, data-sharing capabilities, and extensibility.

Qlik Sense has helped organizations improve data literacy, reduce time consumed in complex reports, and provide widely available MI to senior stakeholders. It also enables self-service analytics, improves data quality and governance, enhances collaboration, and reduces costs.

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

March 2026

Free Report: Azure Data Factory vs. Qlik Compose

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