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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
6.7
Number of Reviews
96
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) (34th)
 

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 8.1% 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 0.5% since last year.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.3%
Informatica Intelligent Data Management Cloud (IDMC)3.7%
SSIS3.6%
Other90.4%
Data Integration
Integration Platform as a Service (iPaaS) Mindshare Distribution
ProductMindshare (%)
Magic xpi Integration Platform1.1%
Boomi iPaaS6.9%
MuleSoft Anypoint Platform6.7%
Other85.3%
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

"The data is more scalable."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"I like Azure Data Factory, it works quite well."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"Azure Data Factory was not difficult to deploy because it is a small area, so we completed it very quickly."
"Data Factory lets us consolidate those steps into a single pipeline."
"I can do everything I want with SSIS and Azure Data Factory."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"The stability of the solution is OK."
 

Cons

"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."
"I do not have any notes for improvement."
"Real-time replication is required, and this is not a simple task."
"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."
"Some of the optimization techniques are not scalable."
"The product integration with advanced coding options could cater to users needing more customization."
"The only challenge with Azure Data Factory is its exception-handling mechanism."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"It is not performing well."
"It does not perform well. It needs more reusable components that are unlimited in time."
 

Pricing and Cost Advice

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"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."
"It's not particularly expensive."
"I don't see a cost; it appears to be included in general support."
"ADF is cheaper compared to AWS."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"Pricing appears to be reasonable in my opinion."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
Construction Company
6%
Construction Company
24%
Printing Company
13%
Outsourcing Company
11%
Financial Services Firm
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
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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