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 #5 in DI , with an average rating of 7.9, and holds a 2.3% mindshare in the category. Magic Software is ranked #33 in PaaS , and holds a 1.1% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution.

Azure Data Factory

Read 96 Azure Data Factory reviews

14,099 Views
9,728 Comparison Views

92% willing to recommend

Magic xpi Integration Platform

Read 1 Magic xpi Integration Platform review

1,218 Views
597 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 Informatica, Microsoft, Palantir and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: July 2026).

Buyer's Guide

Data Integration

July 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

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (5th), Cloud Data Warehouse (7th)

Magic xpi Integration Platform

Average Rating

3.0

Number of Reviews

Ranking in other categories

Integration Platform as a Service (iPaaS) (33rd)

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 2.3%, down 7.2% compared to last year.
Magic xpi Integration Platform, on the other hand, focuses on Integration Platform as a Service (iPaaS), holds 1.1% mindshare, up 0.6% since last year.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.3%
Informatica Intelligent Data Management Cloud (IDMC)	3.8%
SSIS	3.7%
Other	90.2%

Data Integration

Integration Platform as a Service (iPaaS) Mindshare Distribution
Product	Mindshare (%)
Magic xpi Integration Platform	1.1%
Boomi iPaaS	7.0%
MuleSoft Anypoint Platform	6.7%
Other	85.2%

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

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

"The best part of this product is the extraction, transformation, and load."

"An excellent tool for pipeline orchestration."

"Azure Data Factory is a low code, no code platform, which is helpful."

"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."

"It has big potential, especially as a PaaS offering."

"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."

"The reason that we implemented this product is for the full integration with the whole Azure environment."

More Azure Data Factory pros

"The stability of the solution is OK."

Cons

"The speed and performance need to be improved."

"The support and the documentation can be improved."

"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."

"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."

"Technical support isn't the best, as it's a bit delayed at times. Whenever we need some urgent support, wherein we have to restart or something has stuck, it takes a bit of time."

"If the user interface was more user friendly and there was better error feedback, it would be helpful."

"I would like to be informed about the changes ahead of time, so we are aware of what's coming."

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

More Azure Data Factory cons

"It does not perform well. It needs more reusable components that are unlimited in time."

"It is not performing well."

Pricing and Cost Advice

"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."

"Data Factory is expensive."

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."

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

"This is a cost-effective solution."

"Pricing appears to be reasonable in my opinion."

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

More Azure Data Factory pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Manufacturing Company

Computer Software Company

Construction Company

26%

Printing Company

13%

Outsourcing Company

11%

Financial Services Firm

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	63

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...

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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 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 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

MuleSoft Anypoint Platform vs Magic xpi Integration Platform

Compared 20% of the time

Qlik Talend Cloud vs Magic xpi Integration Platform

Compared 18% of the time

Rocket LegaSuite vs Magic xpi Integration Platform

Compared 10% of the time

BMC AMI DevX vs Magic xpi Integration Platform

Compared 10% of the time

Boomi iPaaS vs Magic xpi Integration Platform

Compared 6% of the time

More Magic xpi Integration Platform Competitors

Product Reports

Buyer's Guide

Azure Data Factory

August 2026

Download Azure Data Factory product report

Buyer's Guide

Integration Platform as a Service (iPaaS)

July 2026

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 provides seamless connectivity and automation for businesses seeking efficient integration of their software applications across diverse systems.

Magic xpi offers a robust environment for developing integration projects with its code-free approach. It supports a wide array of connectivity options and enhances efficiency by automating business processes. By leveraging its versatility, it connects cloud services with on-premise systems, thus enabling comprehensive integration capabilities.

What are the most important features of Magic xpi Integration Platform?

Code-free Integration: Simplifies complex integrations with a visual drag-and-drop interface.
Comprehensive Connectivity: Ensures broad connectivity options for various systems and platforms.
Business Process Automation: Streamlines workflows by automating routine tasks.
Robust Security: Incorporates measures to protect data across integrated systems.
Scalability: Offers a scalable solution to accommodate growing business requirements.

What benefits should users look for in reviews?

Efficiency: Users report improved operational efficiency with streamlined integration.
Cost-effectiveness: Lowers long-term costs through automation and reduced manual intervention.
Flexibility: Adapts to specific business needs with customizable options and integrations.
Support and Reliability: Offers strong vendor support and reliable performance according to users.

Magic xpi is implemented widely in industries such as manufacturing, retail, and healthcare. It enables manufacturers to optimize supply chains, retailers to synchronize online and offline operations, and healthcare providers to integrate patient management systems. Its industry-specific adaptations make it an ideal choice for addressing targeted business challenges.

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

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