Azure Data Factory vs FME comparison

Microsoft and Safe Software are both solutions in the Data Integration category. Microsoft is ranked #3 with an average rating of 8.2, while Safe Software is ranked #26 with an average rating of 8.0. Microsoft holds a 3.2% mindshare in DI, compared to Safe Software’s 1.3% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Safe Software users who would recommend it.

Azure Data Factory

Read 93 Azure Data Factory reviews

11,197 Views
7,838 Comparison Views

92% willing to recommend

FME

Read 7 FME reviews

2,569 Views
2,004 Comparison Views

100% willing to recommend

Azure Data Factory

FME

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Executive SummaryUpdated on Dec 19, 2024

FME and Azure Data Factory are prominent contenders in the data integration and automation field. While Azure Data Factory is often deemed superior due to its comprehensive native integrations and scalability, FME gains attention for its more attractive pricing options.

Features: FME is recognized for its spatial data transformation capabilities and flexibility with different data formats, offering an intuitive graphical user interface and robust support for spatial analysis. Azure Data Factory is strong in data orchestration and integration with excellent cloud and hybrid support, providing a seamless ETL experience with over 100 built-in connectors, data transformation capabilities, and powerful pipeline management.

Room for Improvement: FME could improve its scalability options and enhance its cloud integration features to compete better with larger data solutions. Additionally, supporting more advanced data orchestration tools would be beneficial. Azure Data Factory might focus on simplifying its complex deployment process, enhancing support for varied data sources, and expanding its customer service offerings to be more personalized.

Ease of Deployment and Customer Service: FME offers a simpler deployment process enhanced by comprehensive support services, which ease the implementation for users. It is known for being user-friendly, providing quick setup options. Azure Data Factory, while having a more intricate deployment process, benefits from its strong cloud-native support system which is ideal for handling complex enterprise-level deployments, offering solid backend support but requiring significant expertise for initial setup.

Pricing and ROI: FME generally provides lower upfront costs, appealing to businesses seeking advanced data transformation without substantial investment. Its cost-effective nature makes it suitable for smaller companies. In contrast, Azure Data Factory's pricing aligns with its broad feature set, often necessitating higher initial investment but promising a higher return on investment for large enterprises with demands for extensive scalability and robust cloud infrastructure.

To learn more, read our detailed Azure Data Factory vs. FME Report (Updated: December 2025).

Buyer's Guide

Azure Data Factory vs. FME

December 2025

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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

Ranking in other categories

Cloud Data Warehouse (2nd)

FME

Ranking in Data Integration

26th

Average Rating

8.6

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.2%, down from 10.0% compared to the previous year. The mindshare of FME is 1.3%, down from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
Azure Data Factory	3.2%
FME	1.3%
Other	95.5%

Data Integration

Featured Reviews

KandaswamyMuthukrishnan

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.

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Gert Booysen

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.

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Quotes from Members

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

Pros

"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."

"Data Factory's best features are simplicity and flexibility."

"The function of the solution is great."

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."

"The most valuable feature is the ease in which you can create an ETL pipeline."

"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."

"The most valuable aspect is the copy capability."

More Azure Data Factory pros

"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."

"It has standard plug-ins available for different data sources."

"FME is spatially aware and understands how to deal with the conversion of spatial objects and their attributes."

"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."

"From my reseller perspective, the best features in FME are the ease of operation and the fact that it works."

Cons

"The user interface could use improvement. It's not a major issue but it's something that can be improved."

"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."

"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."

"The speed and performance need to be improved."

"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."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"Data Factory's cost is too high."

"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."

More Azure Data Factory cons

"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."

"Improvements could be made to mapping presentations."

"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."

"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

"The solution's pricing is competitive."

"I would not say that this product is overly expensive."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"Pricing is comparable, it's somewhere in the middle."

"It's not particularly expensive."

"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."

More Azure Data Factory pricing and cost advice

"The product's price is reasonable."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

11%

Manufacturing Company

Government

32%

Energy/Utilities Company

13%

Computer Software Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	19
Large Enterprise	57

By reviewers
Company Size	Count
Small Business	2
Midsize Enterprise	1
Large Enterprise	4

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.

See all answers

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...

See all answers

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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What needs improvement with FME?

See all answers

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...

See all answers

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.

See all answers

Comparisons

Snowflake vs Azure Data Factory

Compared 7% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 6% of the time

Palantir Foundry vs Azure Data Factory

Compared 5% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 4% of the time

Informatica PowerCenter vs Azure Data Factory

Compared 4% of the time

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SSIS vs FME

Compared 10% of the time

Alteryx Designer vs FME

Compared 7% of the time

MuleSoft Anypoint Platform vs FME

Compared 6% of the time

Boomi iPaaS vs FME

Compared 5% of the time

Qlik Talend Cloud vs FME

Compared 4% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

January 2026

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Buyer's Guide

FME

January 2026

Download FME product report

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

FME is the data integration platform with the best support for spatial data. Run workflows on the desktop or deploy them in a server or cloud environment.

Safe Software

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

Buyer's Guide

Azure Data Factory vs. FME

December 2025

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