Azure Data Factory vs FME comparison

Microsoft and Safe Software are both solutions in the Data Integration category. Microsoft is ranked #4 with an average rating of 8.2, while Safe Software is ranked #31 with an average rating of 8.0. Microsoft holds a 2.4% mindshare in DI, compared to Safe Software’s 1.1% 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

12,241 Views
8,446 Comparison Views

92% willing to recommend

FME

Read 7 FME reviews

3,094 Views
2,382 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: April 2026).

Buyer's Guide

Azure Data Factory vs. FME

April 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

4th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (5th)

FME

Ranking in Data Integration

31st

Average Rating

8.6

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.4%, down from 8.6% compared to the previous year. The mindshare of FME is 1.1%, down from 1.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.4%
FME	1.1%
Other	96.5%

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

"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."

"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."

"The scalability of the product is impressive."

"In terms of my personal experience, it works fine."

"It's a good tool, a good product that does what it's supposed to do well, which is ingesting data from a source to your target, to another cloud, to another source."

"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."

"Azure Data Factory became more user-friendly when data-flows were introduced."

"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."

More Azure Data Factory pros

"FME's features that I have found most valuable are that it has a very friendly user interface, you don't need to use a lot of code, it has a lot of connectors and few forms, and it has a strong facial aspect that can do a lot of facial analysis."

"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."

"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."

"The most valuable feature of FME is the graphical user interface."

"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."

More FME pros

Cons

"In the next release, it's important that some sort of scheduler for running tasks is added."

"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."

"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."

"The stability of Azure as a PaaS could be improved."

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

"The deployment should be easier."

"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."

"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."

"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."

"To get a higher rating, it would have to improve the price and the associated scalability. These are the main issues."

"FME is a great tool, but I don't know if we can scale it up since the prices are high and we would need to convince the decision makers to provide more budget."

"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."

Pricing and Cost Advice

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

"ADF is cheaper compared to AWS."

"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."

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

"This is a cost-effective solution."

"I would rate Data Factory's pricing nine out of ten."

"The licensing is a pay-as-you-go model, where you pay for what you consume."

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

More Azure Data Factory pricing and cost advice

"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

12%

Computer Software Company

10%

Manufacturing Company

Government

29%

Energy/Utilities Company

13%

Construction Company

Comms Service Provider

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...

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...

See all answers

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

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

Compared 5% of the time

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

Jitterbit Harmony vs Azure Data Factory

Compared 2% of the time

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SSIS vs FME

Compared 9% of the time

Alteryx Designer vs FME

Compared 5% of the time

Qlik Talend Cloud vs FME

Compared 5% of the time

MuleSoft Anypoint Platform vs FME

Compared 4% of the time

Ikon vs FME

Compared 4% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

May 2026

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Buyer's Guide

FME

May 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 a powerful tool designed for efficient geospatial data handling, supporting over 400 file formats and integrating with diverse systems. Its intuitive interface facilitates seamless automation of workflows, making it ideal for sectors that manage large spatial data volumes.

With FME, businesses automate data flows and manage GIS data transfers while integrating with tools like GE Smallworld. It empowers users with self-service capabilities for data processing and real-time event management. Despite its strengths, users note areas for improvement such as better mapping presentations, simpler loops, and more guidance on geographical transformations. Pricing remains a consideration for some markets. However, FME is a robust solution for massive data transformations, network infrastructure management, and automation of data quality control, especially in governmental contexts.

What are FME's key features?

Spatial Capabilities: Efficient handling of geospatial data through triggers and automation.
Integration: Seamlessly works with FME Flow, FME Form, and scripting languages like Python.
User-Friendly Interface: Simplifies data transformation and debugging without extensive coding.
Format Support: Over 400 file formats ensure wide-ranging compatibility.
System Integration: Connects with numerous systems, preferred for large spatial data volumes.

What benefits should users consider?

Automation: Streamlines workflows and reduces manual intervention.
Efficiency: Handles large datasets effectively, optimizing data operations.
Cost-Effectiveness: Despite pricing concerns, offers significant functionality for data processing.
Self-Service Capabilities: Enables users to manage and transform data independently.
Real-Time Processing: Supports real-time event handling for dynamic environments.

FME is widely adopted across industries that require precise geospatial data management such as government agencies needing to automate and control data processes efficiently or organizations handling complex network infrastructures that engage in frequent GIS data transfers. Its capacity for seamless integration with various systems enables practical use for extensive data transformations and automation, increasing operational efficiency in data-intensive sectors.

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

April 2026

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