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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 (2nd)
FME
Ranking in Data Integration
23rd
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 June 2025, in the Data Integration category, the mindshare of Azure Data Factory is 8.4%, down from 12.3% compared to the previous year. The mindshare of FME is 1.9%, up from 1.6% 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

"In terms of my personal experience, it works fine."
"The overall performance is quite good."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"The trigger scheduling options are decently robust."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."
"The solution is okay."
"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."
"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."
"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."
"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."
"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."
 

Cons

"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"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."
"Data Factory's cost is too high."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"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."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"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."
"We are looking at the possibility of using Glue instead of FME, using the native AWS product."
"Improvements could be made to mapping presentations."
"To get a higher rating, it would have to improve the price and the associated scalability. These are the main issues."
"FME's price needs improvement for the African market."
"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."
 

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."
"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."
"The pricing is a bit on the higher end."
"It's not particularly expensive."
"The cost is based on the amount of data sets that we are ingesting."
"The price you pay is determined by how much you use it."
"The licensing cost is included in the Synapse."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"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
12%
Manufacturing Company
9%
Government
6%
Government
30%
Energy/Utilities Company
13%
Computer Software Company
7%
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: June 2025.
856,873 professionals have used our research since 2012.