Azure Data Factory vs Magic xpi Integration Platform comparison

Why PeerSpot?

The compared Microsoft and Magic Software solutions aren't in the same category. Microsoft is ranked #5 in DI , with an average rating of 8.0, and holds a 2.2% 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 97 Azure Data Factory reviews

14,793 Views
10,207 Comparison Views

92% willing to recommend

Magic xpi Integration Platform

Read 1 Magic xpi Integration Platform review

1,336 Views
681 Comparison Views

0% willing to recommend

Azure Data Factory

Magic xpi Integration Platform

Comparison Buyer's Guide

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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, Palantir, Microsoft and others in Data Integration.

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

Buyer's Guide

Data Integration

September 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 2.2%, down 5.5% 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 0.7% since last year.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.2%
Informatica Intelligent Data Management Cloud (IDMC)	3.7%
SSIS	3.6%
Other	90.5%

Data Integration

Integration Platform as a Service (iPaaS) Mindshare Distribution
Product	Mindshare (%)
Magic xpi Integration Platform	1.1%
Boomi iPaaS	6.8%
MuleSoft Anypoint Platform	6.5%
Other	85.6%

Integration Platform as a Service (iPaaS)

Featured Reviews

Kunal Das

Test Engineer at Happiest Minds Technologies

Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling

If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.

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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 data is more scalable."

"Data Factory lets us consolidate those steps into a single pipeline."

"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."

"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."

"It is beneficial that the solution is written with Spark as the back end."

"The solution can scale very easily."

"The most valuable feature of this solution would be ease of use."

"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."

More Azure Data Factory pros

"The stability of the solution is OK."

Cons

"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."

"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."

"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."

"I would like to see this time travel feature in Snowflake added to Azure Data Factory."

"Understanding the pricing model for Data Factory is quite complex. It needs to be simplified, and easier to understand."

"It would be better if it had machine learning capabilities."

"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."

"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."

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

"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."

"The solution is cheap."

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

"The licensing cost is included in the Synapse."

"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."

"Product is priced at the market standard."

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

"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

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	64

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 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 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

MuleSoft Anypoint Platform vs Magic xpi Integration Platform

Compared 16% of the time

Qlik Talend Cloud vs Magic xpi Integration Platform

Compared 14% of the time

TIBCO Spotfire vs Magic xpi Integration Platform

Compared 8% of the time

BMC AMI DevX vs Magic xpi Integration Platform

Compared 8% of the time

Boomi iPaaS vs Magic xpi Integration Platform

Compared 5% of the time

More Magic xpi Integration Platform Competitors

Product Reports

Buyer's Guide

Azure Data Factory

September 2026

Download Azure Data Factory product report

Buyer's Guide

Integration Platform as a Service (iPaaS)

September 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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