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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
6.8
Number of Reviews
94
Ranking in other categories
Data Integration (4th), Cloud Data Warehouse (5th)
Magic xpi Integration Platform
Average Rating
3.0
Number of Reviews
1
Ranking in other categories
Integration Platform as a Service (iPaaS) (32nd)
 

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 2.4%, down 8.6% compared to last year.
Magic xpi Integration Platform, on the other hand, focuses on Integration Platform as a Service (iPaaS), holds 1.2% mindshare, up 0.5% since last year.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.4%
SSIS3.7%
Informatica Intelligent Data Management Cloud (IDMC)3.6%
Other90.3%
Data Integration
Integration Platform as a Service (iPaaS) Mindshare Distribution
ProductMindshare (%)
Magic xpi Integration Platform1.2%
Boomi iPaaS7.2%
MuleSoft Anypoint Platform7.0%
Other84.6%
Integration Platform as a Service (iPaaS)
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
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.
it_user977634 - PeerSpot reviewer
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…

Quotes from Members

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

Pros

"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."
"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
"The overall performance is quite good."
"When it comes to our business requirements, this solution has worked well for us."
"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."
"It makes it easy to collect data from different sources."
"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."
"The data copy template is a valuable feature, and with the pipeline template, it takes only a few clicks for the on-premises data to come in."
"The stability of the solution is OK."
"The stability of the solution is OK."
 

Cons

"I wouldn't consider it to be stable since it fails at times."
"The Microsoft documentation is too complicated."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."
"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."
"To my mind, the solution needs to be more connectable to its own services."
"It does not perform well. It needs more reusable components that are unlimited in time."
"It is not performing well."
 

Pricing and Cost Advice

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"I would not say that this product is overly expensive."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"The price is fair."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"ADF is cheaper compared to AWS."
"Pricing is comparable, it's somewhere in the middle."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
9%
Government
6%
Construction Company
20%
Printing Company
13%
Outsourcing Company
11%
Computer Software Company
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise61
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...
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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
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