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 #29 with an average rating of 8.0. Microsoft holds a 2.8% mindshare in DI, compared to Safe Software’s 1.2% 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 94 Azure Data Factory reviews

10,752 Views
7,526 Comparison Views

92% willing to recommend

FME

Read 7 FME reviews

2,678 Views
2,062 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: March 2026).

Buyer's Guide

Azure Data Factory vs. FME

March 2026

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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

29th

Average Rating

8.6

Reviews Sentiment

6.5

Number of Reviews

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
Product	Mindshare (%)
Azure Data Factory	2.8%
FME	1.2%
Other	96.0%

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

"The function of the solution is great."

"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."

"The security of the agent that is installed on-premises is very good."

"An excellent tool for pipeline orchestration."

"It's extremely consistent."

"It is easy to integrate."

"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."

"The data is more scalable."

More Azure Data Factory pros

"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."

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

"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

"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."

"Some prebuilt data source or data connection aspects are generic."

"We require Azure Data Factory to be able to connect to Google Analytics."

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

"When working with AWS, we have noticed that the difference between ADF and AWS is that AWS is more customer-focused. They're more responsive compared to any other company. ADF is not as good as AWS, but it should be. If AWS is ten out of ten, ADF is around eight out of ten. I think AWS is easier to understand from the GUI perspective compared to ADF."

"It does not appear to be as rich as other ETL tools. It has very limited capabilities."

"The solution needs to be more connectable to its own services."

"If the user interface was more user friendly and there was better error feedback, it would be helpful."

More Azure Data Factory cons

"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 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."

"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's price needs improvement for the African market."

Pricing and Cost Advice

"The price you pay is determined by how much you use it."

"This is a cost-effective solution."

"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."

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

"Pricing appears to be reasonable in my opinion."

"The pricing model is based on usage and is not cheap."

"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."

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

More Azure Data Factory pricing and cost advice

"FME Server used to cost £10,000; now it can cost over £100,000."

"The product's price is reasonable."

"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

12%

Computer Software Company

11%

Manufacturing Company

Government

32%

Energy/Utilities Company

13%

Comms Service Provider

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	20
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...

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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...

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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

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Compared 5% of the time

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Compared 4% of the time

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Compared 3% of the time

Informatica PowerCenter vs Azure Data Factory

Compared 3% of the time

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Compared 9% of the time

MuleSoft Anypoint Platform vs FME

Compared 5% of the time

Qlik Talend Cloud vs FME

Compared 5% of the time

Alteryx Designer vs FME

Compared 5% of the time

Boomi iPaaS vs FME

Compared 4% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

March 2026

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Buyer's Guide

FME

March 2026

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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

March 2026

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