Azure Data Factory vs Qlik Compose comparison

Microsoft and Qlik are both solutions in the Data Integration category. Microsoft is ranked #4 with an average rating of 8.1, while Qlik is ranked #48. Microsoft holds a 2.4% mindshare in DI, compared to Qlik’s 0.9% 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

11,377 Views
7,850 Comparison Views

92% willing to recommend

Qlik Compose

Read 12 Qlik Compose reviews

1,942 Views
1,670 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: April 2026).

Buyer's Guide

Azure Data Factory vs. Qlik Compose

April 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

4th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (5th)

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 2.4%, down from 9.2% 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 Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.4%
Qlik Compose	0.9%
Other	96.7%

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.

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 solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."

"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS"

"The data is more scalable."

"The most valuable feature I have found at Azure Data Factory is the data flow function."

"Azure Data Factory became more user-friendly when data-flows were introduced."

"The solution is okay."

"From what we have seen so far, the solution seems very stable."

"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."

More Azure Data Factory pros

"The technical support is very good. I rate the technical support a ten out of ten."

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

"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."

"As long as you pick the solution that best fits with your requirements, you won't find that performance is a problem."

"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."

"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."

More Qlik Compose pros

Cons

"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."

"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."

"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."

"As far as customer service and support with Azure Data Factory, we are not always satisfied with the response time."

"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."

"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."

"We require Azure Data Factory to be able to connect to Google Analytics."

"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."

More Azure Data Factory cons

"There could be more customization options."

"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."

"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."

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

"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."

"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."

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

More Qlik Compose cons

Pricing and Cost Advice

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

"Understanding the pricing model for Data Factory is quite complex."

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

"Pricing is comparable, it's somewhere in the middle."

"ADF is cheaper compared to AWS."

"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."

"Data Factory is affordable."

"I don't see a cost; it appears to be included in general support."

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

12%

Government

11%

Construction Company

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

Databricks 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 8% of the time

WhereScape RED vs Qlik Compose

Compared 7% of the time

Airbyte Cloud vs Qlik Compose

Compared 5% of the time

More Qlik Compose Competitors

Product Reports

Buyer's Guide

Azure Data Factory

April 2026

Download Azure Data Factory product report

Buyer's Guide

Qlik Compose

April 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

April 2026

Free Report: Azure Data Factory vs. Qlik Compose

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