Try our new research platform with insights from 80,000+ expert users

Azure Data Factory vs Magic xpi Integration Platform comparison

 

Comparison Buyer's Guide

Executive Summary

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
7.0
Number of Reviews
91
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (2nd)
Magic xpi Integration Platform
Average Rating
3.0
Number of Reviews
1
Ranking in other categories
Integration Platform as a Service (iPaaS) (24th)
 

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 8.4%, down 12.3% compared to last year.
Magic xpi Integration Platform, on the other hand, focuses on Integration Platform as a Service (iPaaS), holds 0.5% mindshare, up 0.3% since last year.
Data Integration
Integration Platform as a Service (iPaaS)
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
it_user977634 - PeerSpot reviewer
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…

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"In terms of my personal experience, it works fine."
"The solution handles large volumes of data very well. One of its best features is its ability to integrate data end-to-end, from pulling data from the source to accessing Databricks. This makes it quite useful for our needs."
"The scalability of the product is impressive."
"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"The flexibility that Azure Data Factory offers is great."
"The trigger scheduling options are decently robust."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"The stability of the solution is OK."
 

Cons

"There is a problem with the integration with third-party solutions, particularly with SAP."
"The one element of the solution that we have used and could be improved is the user interface."
"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."
"There is no built-in pipeline exit activity when encountering an error."
"The product could provide more ways to import and export data."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"There are limitations when processing more than one GD file."
"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."
"It is not performing well."
 

Pricing and Cost Advice

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"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 don't see a cost; it appears to be included in general support."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"The pricing is a bit on the higher end."
"ADF is cheaper compared to AWS."
"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."
"It's not particularly expensive."
Information not available
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
856,873 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
Retailer
14%
Printing Company
14%
Computer Software Company
12%
Performing Arts
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
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.
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...
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...
Ask a question
Earn 20 points
 

Also Known As

No data available
Magic xpi Integration Platform, iBOLT
 

Overview

 

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: June 2025.
856,873 professionals have used our research since 2012.