Azure Data Factory vs Magic xpi Integration Platform comparison

The compared Microsoft and Magic Software solutions aren't in the same category. Microsoft is ranked #1 in DI , with an average rating of 8.2, and holds a 5.6% mindshare in the category. Magic Software is ranked #27 in PaaS , and holds a 0.7% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution.

Azure Data Factory

Read 92 Azure Data Factory reviews

14,334 Views
10,034 Comparison Views

92% willing to recommend

Magic xpi Integration Platform

Read 1 Magic xpi Integration Platform review

504 Views
96 Comparison Views

0% willing to recommend

Azure Data Factory

Magic xpi Integration Platform

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Executive Summary

We performed a comparison between Azure Data Factory and Magic xpi Integration Platform based on real PeerSpot user reviews.

Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: September 2025).

Buyer's Guide

Data Integration

September 2025

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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

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Integration (1st), Cloud Data Warehouse (2nd)

Magic xpi Integration Platform

Average Rating

3.0

Number of Reviews

Ranking in other categories

Integration Platform as a Service (iPaaS) (27th)

Mindshare comparison

Azure Data Factory and Magic xpi Integration Platform aren’t in the same category and serve different purposes. Azure Data Factory is designed for Data Integration and holds a mindshare of 5.6%, down 11.6% compared to last year.
Magic xpi Integration Platform, on the other hand, focuses on Integration Platform as a Service (iPaaS), holds 0.7% mindshare, up 0.3% since last year.

Data Integration Market Share Distribution
Product	Market Share (%)
Azure Data Factory	5.6%
Informatica PowerCenter	6.3%
SSIS	5.9%
Other	82.2%

Data Integration

Integration Platform as a Service (iPaaS) Market Share Distribution
Product	Market Share (%)
Magic xpi Integration Platform	0.7%
Microsoft Azure Logic Apps	13.1%
Boomi iPaaS	12.4%
Other	73.8%

Integration Platform as a Service (iPaaS)

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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it_user977634

Enterprise IT Architect at a consumer goods company with 1,001-5,000 employees

A low-performing integration tool

We use it as an in-house back-type integration tool. It allows us to have different integrations between different systems It does not perform well. It needs more reusable components that are unlimited in time. Furthermore, it relies on the files systems and does not create components, so it is…

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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

"The trigger scheduling options are decently robust."

"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."

"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."

"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."

"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."

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

"It is easy to deploy workflows and schedule jobs."

"The solution can scale very easily."

More Azure Data Factory pros

"The stability of the solution is OK."

Cons

"Azure Data Factory uses many resources and has issues with parallel workflows."

"There is no built-in pipeline exit activity when encountering an error."

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."

"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."

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

"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."

"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."

More Azure Data Factory cons

"It is not performing well."

Pricing and Cost Advice

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

"The licensing cost is included in the Synapse."

"This is a cost-effective solution."

"Product is priced at the market standard."

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

"I would not say that this product is overly expensive."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

More Azure Data Factory pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Government

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	19
Large Enterprise	55

No data available

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...

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Comparisons

Snowflake vs Azure Data Factory

Compared 8% of the time

Informatica PowerCenter vs Azure Data Factory

Compared 6% of the time

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

Compared 6% of the time

Palantir Foundry vs Azure Data Factory

Compared 5% of the time

FME vs Azure Data Factory

Compared 5% of the time

More Azure Data Factory Competitors

MuleSoft Anypoint Platform vs Magic xpi Integration Platform

Compared 25% of the time

Rocket LegaSuite vs Magic xpi Integration Platform

Compared 19% of the time

Informatica Data Engineering Streaming vs Magic xpi Integration Platform

Compared 18% of the time

Boomi iPaaS vs Magic xpi Integration Platform

Compared 16% of the time

More Magic xpi Integration Platform Competitors

Product Reports

Buyer's Guide

Azure Data Factory

September 2025

Download Azure Data Factory product report

Buyer's Guide

Integration Platform as a Service (iPaaS)

August 2025

Download Magic xpi Integration Platform product report

Also Known As

No data available

Magic xpi Integration Platform, iBOLT

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

Magic xpi Integration Platform is a total solution for integrating, automating and transforming the data of your business applications. The intuitive and easy-to-use interface, including 100+ pre-built connectors, makes it ideal for all types of users, from business users and citizen integrators to IT experts. Magic’s end-to-end tailored solutions are a great fit for all types of IT infrastructures, supporting all of the on-premise, cloud and hybrid integration needs of organizations around the world.

Magic Software

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

Godrej Properties

Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration. Updated: September 2025.

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