Azure Data Factory vs FME comparison

Microsoft and Safe Software are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.1, while Safe Software is ranked #26 with an average rating of 8.7. Microsoft holds a 11.0% mindshare in DI, compared to Safe Software’s 2.0% 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 86 Azure Data Factory reviews

21,615 Views
17,232 Comparison Views

92% willing to recommend

FME

Read 5 FME reviews

2,791 Views
2,095 Comparison Views

100% willing to recommend

Azure Data Factory

FME

Comparison Buyer's Guide

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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 2024).

Buyer's Guide

Azure Data Factory vs. FME

December 2024

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Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

FME

Ranking in Data Integration

26th

Average Rating

8.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of December 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.0%, down from 13.3% compared to the previous year. The mindshare of FME is 2.0%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

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.

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Alan Bloor

Geographic Information System Developer at Public Sector

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.

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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 solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."

"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."

"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."

"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."

"The data flows were beneficial, allowing us to perform multiple transformations."

"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."

"I am one hundred percent happy with the stability."

"Its integrability with the rest of the activities on Azure is most valuable."

More Azure Data Factory pros

"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."

"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."

"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

"Azure Data Factory's pricing in terms of utilization could be improved."

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

"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."

"The one element of the solution that we have used and could be improved is the user interface."

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

"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."

"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."

"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."

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."

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

"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."

"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

"Data Factory is affordable."

"Understanding the pricing model for Data Factory is quite complex."

"The price is fair."

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

"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."

"The licensing cost is included in the Synapse."

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

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

More Azure Data Factory pricing and cost advice

"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."

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

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824,053 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Government

28%

Energy/Utilities Company

12%

Computer Software Company

Manufacturing Company

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.

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 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.

See all answers

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...

See all answers

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...

See all answers

Comparisons

Informatica PowerCenter vs Azure Data Factory

Compared 13% of the time

Snowflake vs Azure Data Factory

Compared 10% of the time

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

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

Oracle GoldenGate vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Talend Open Studio vs FME

Compared 16% of the time

Alteryx Designer vs FME

Compared 14% of the time

SSIS vs FME

Compared 9% of the time

Informatica PowerCenter vs FME

Compared 6% of the time

AWS Glue vs FME

Compared 5% of the time

More FME Competitors

Product Reports

Buyer's Guide

Azure Data Factory

December 2024

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Buyer's Guide

FME

December 2024

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Microsoft

Safe Software

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.

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.

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 2024

Free Report: Azure Data Factory vs. FME

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