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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
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Cloud Data Warehouse (2nd)
FME
Ranking in Data Integration
29th
Average Rating
8.6
Reviews Sentiment
6.5
Number of Reviews
7
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.8%, down from 9.7% compared to the previous year. The mindshare of FME is 1.2%, down from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.8%
FME1.2%
Other96.0%
Data Integration
 

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.
Gert Booysen - PeerSpot reviewer
Software Solutions Leader at GE Vernova
Extensive format support and reliable integration enhance data management while new pricing model requires reassessment
I haven't had any input or requirements from any customers that are not currently covered, so I don't have any additional needs that were identified or raised to me. Regarding pricing, with the model changes that they've implemented a while back, it actually made it more expensive to use, especially on the server side. They changed the licensing model, and that made customers think it is overpriced. Some customers were actually looking at alternatives. Pricing with the model changes was perceived negatively. I work primarily with enterprise customers, Vodacom, Eskom, so it's tier-one customers. For small customers, this solution is a bit too expensive. They don't really use it and just do direct integration on smaller implementations. This is basically used by tier-one customers. FME is still able to save time and money for clients. It's still a good investment. Regarding similar products to FME, GE developed a product called Data Fabric. That is a real-time operational integration platform, Data Fabric Network Connect, which is a GE Grid OS product. It is actually more expensive than FME, but the purpose is different as it's operational. The vendor in this case is GE, and it's a company that we bought that used to be called Greenbird. In current use scenarios, FME is still leading compared to Data Fabric. The GE product has a different application.

Quotes from Members

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

Pros

"The most important feature is that it can help you do the multi-threading concepts."
"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."
"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS"
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"Powerful but easy-to-use and intuitive."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"Azure Data Factory is a low code, no code platform, which is helpful."
"Data Factory's most valuable feature is Copy Activity."
"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."
"It has standard plug-ins available for different data sources."
"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."
"From my reseller perspective, the best features in FME are the ease of operation and the fact that it works."
"FME is spatially aware and understands how to deal with the conversion of spatial objects and their attributes."
"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."
"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."
 

Cons

"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"The solution needs to be more connectable to its own services."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"The setup and configuration process could be simplified."
"The product integration with advanced coding options could cater to users needing more customization."
"Some prebuilt data source or data connection aspects are generic."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"I do not have any notes for improvement."
"To get a higher rating, it would have to improve the price and the associated scalability. These are the main issues."
"Improvements could be made to mapping presentations."
"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."
"We are looking at the possibility of using Glue instead of FME, using the native AWS product."
"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

"Product is priced at the market standard."
"This is a cost-effective solution."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"It's not particularly expensive."
"Data Factory is expensive."
"I don't see a cost; it appears to be included in general support."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"FME Server used to cost £10,000; now it can cost over £100,000."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Government
32%
Energy/Utilities Company
13%
Comms Service Provider
6%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise20
Large Enterprise57
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise1
Large Enterprise4
 

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 needs improvement with FME?
I haven't had any input or requirements from any customers that are not currently covered, so I don't have any additional needs that were identified or raised to me. Regarding pricing, with the mod...
What is your primary use case for FME?
The use cases for FME are mainly integration to the GE Smallworld product. GE Smallworld is a GE product, and we are using it to integrate with other third-party products into GE Smallworld and ADM...
What advice do you have for others considering FME?
The overall rating for FME is eight out of ten, and I prefer the feedback to be anonymous. My job title is Senior Solutions Architect.
 

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: March 2026.
884,873 professionals have used our research since 2012.