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 lets us consolidate those steps into a single pipeline."

"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."

"Azure Data Factory is great because it's a cloud service; you do not have to take care of the installation and configuration yourself."

"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."

"Synapse was the better choice for us to implement, as it has a lot of out-of-the-box connectors that we can utilize for data transformation and organization."

"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."

"Azure Data Factory is easy to use and integrates well, providing good classification to bring data from diverse parts of the data infrastructure, whether from CSV files coming from the Cisco server, MySQL, Excel machines, or local network data from remote files."

"We use the solution to move data from on-premises to the cloud."

More Azure Data Factory pros

"The stability of the solution is OK."

Cons

"The initial setup is not very straightforward."

"It does not appear to be as rich as other ETL tools. It has very limited capabilities."

"But, I feel that if the usage extends beyond a certain threshold, it will start getting expensive."

"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."

"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."

"Data Factory's monitorability could be better."

"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."

"There is one particular problem with Azure Data Factory. When you have a parent-to-child relationship and the child has one more relationship, creating a hierarchy situation, there are issues."

More Azure Data Factory cons

"It is not performing well."

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

Pricing and Cost Advice

"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."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

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

"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."

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

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

"The solution is cheap."

"The price you pay is determined by how much you use it."

More Azure Data Factory pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

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)

August 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

Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration. Updated: July 2026.

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