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Azure Data Factory vs FME comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

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
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Cloud Data Warehouse (3rd)
FME
Ranking in Data Integration
24th
Average Rating
8.6
Reviews Sentiment
6.8
Number of Reviews
6
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2025, in the Data Integration category, the mindshare of Azure Data Factory is 8.9%, down from 12.5% compared to the previous year. The mindshare of FME is 1.8%, up from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

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.
Alan Bloor - PeerSpot reviewer
Great for handling large volumes of data, but it is priced a bit high
When I do coding, I think about every single function. Some of these functions can be very elementary, like doing a substring or some capitalization. But FME removes all that coding because it's a transformer, so the time to develop an application to get to a point where you're producing results is decreased massively. It used to take weeks and months to develop software, and now I can use something like FME, and within one day, we get results. We can look at and validate data. We make minor subtle changes to the workbenches to improve it. We can share the workbenches. We don't have to use GitHub or anything else.

Quotes from Members

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

Pros

"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"The most important feature is that it can help you do the multi-threading concepts."
"The flexibility that Azure Data Factory offers is great."
"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The solution can scale very easily."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"We use the solution to move data from on-premises to the cloud."
"The most valuable feature of FME is the graphical user interface. There is nothing better. It is very easy to debug because you can see all steps where there are failures. Overall the software is easy to optimize a process."
"It has a very friendly user interface. You don't need to use a lot of code. For us that's the most important aspect about it. Also, it has a lot of connectors and few forms. It has a strong facial aspect. It can do a lot of facial analysis."
"We make minor subtle changes to the workbenches to improve it. We can share the workbenches. We don't have to use GitHub or anything else."
"All spatial features are unrivaled, and the possibility to execute them based on a scheduled trigger, manual, e-mail, Websocket, tweet, file/directory change or virtually any trigger is most valuable."
"FME is spatially aware and understands how to deal with the conversion of spatial objects and their attributes."
"It has standard plug-ins available for different data sources."
 

Cons

"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."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"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."
"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."
"Data Factory's cost is too high."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"Some prebuilt data source or data connection aspects are generic."
"We are looking at the possibility of using Glue instead of FME, using the native AWS product."
"To get a higher rating, it would have to improve the price and the associated scalability. These are the main issues."
"The one thing that always appears in the community is the ability to make really easy loops to loop through data efficiently. That needs to be added at some point."
"Improvements could be made to mapping presentations."
"FME can improve the geographical transformation. I've had some problems with the geographical transformations, but it's probably mostly because I'm not the most skilled geographer in-house. The solution requires some in-depth knowledge to perform some functions."
"FME's price needs improvement for the African market."
 

Pricing and Cost Advice

"This is a cost-effective solution."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"The price is fair."
"I would not say that this product is overly expensive."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"The licensing cost is included in the Synapse."
"Pricing is comparable, it's somewhere in the middle."
"Understanding the pricing model for Data Factory is quite complex."
"We used the standard licensing for our use of FME. The cost was approximately €15,000 annually. We always welcome less expensive solutions, if the solution could be less expensive it would be helpful."
"The product's price is reasonable."
"FME Server used to cost £10,000; now it can cost over £100,000."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
13%
Manufacturing Company
9%
Healthcare Company
6%
Government
30%
Energy/Utilities Company
13%
Computer Software Company
8%
Comms Service Provider
6%
 

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...
What do you like most about FME?
We make minor subtle changes to the workbenches to improve it. We can share the workbenches. We don't have to use GitHub or anything else.
What is your experience regarding pricing and costs for FME?
The pricing is really bad. Last year, they rebranded the whole pricing structure. It used to be moderately priced at about £400 per user per year. Now they've changed the whole thing, and it's expe...
What needs improvement with FME?
The one thing that always appears in the community is the ability to make really easy loops to loop through data efficiently. That needs to be added at some point. There must be a technical or comm...
 

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
Shell, US Department of Commerce, PG&E, BC Hydro, City of Vancouver, Enel, Iowa DoT, San Antonio Water System
Find out what your peers are saying about Azure Data Factory vs. FME and other solutions. Updated: April 2025.
851,604 professionals have used our research since 2012.