Azure Data Factory vs FME comparison

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Executive Summary

We performed a comparison between Azure Data Factory and FME based on real PeerSpot user reviews.

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Azure Data Factory vs. FME Report (Updated: March 2024).
765,386 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable.""The security of the agent that is installed on-premises is very good.""It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build.""Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process.""When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit.""I can do everything I want with SSIS and Azure Data Factory.""It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory.""I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."

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"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.""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.""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."

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Cons
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory.""Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters.""On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels.""I have not found any real shortcomings within the product.""Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate.""Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement.""When the record fails, it's tough to identify and log.""The deployment should be easier."

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"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.""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."

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Pricing and Cost Advice
  • "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."
  • "This is a cost-effective solution."
  • "The price you pay is determined by how much you use it."
  • "Understanding the pricing model for Data Factory is quite complex."
  • "I would not say that this product is overly expensive."
  • "The licensing is a pay-as-you-go model, where you pay for what you consume."
  • "Our licensing fees are approximately 15,000 ($150 USD) per month."
  • "The licensing cost is included in the Synapse."
  • 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."
  • More FME Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:AWS Glue and Azure Data factory for ELT best performance cloud services.
    Top Answer: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 and… more »
    Top Answer: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… more »
    Top Answer: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.
    Top Answer: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… more »
    Top Answer: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… more »
    Ranking
    1st
    out of 94 in Data Integration
    Views
    26,364
    Comparisons
    20,689
    Reviews
    40
    Average Words per Review
    495
    Rating
    8.0
    23rd
    out of 94 in Data Integration
    Views
    3,070
    Comparisons
    2,426
    Reviews
    3
    Average Words per Review
    725
    Rating
    8.3
    Comparisons
    Learn More
    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
    Top Industries
    REVIEWERS
    Computer Software Company35%
    Insurance Company12%
    Financial Services Firm8%
    Manufacturing Company8%
    VISITORS READING REVIEWS
    Computer Software Company13%
    Financial Services Firm13%
    Manufacturing Company8%
    Healthcare Company7%
    VISITORS READING REVIEWS
    Government29%
    Energy/Utilities Company10%
    Computer Software Company10%
    Comms Service Provider5%
    Company Size
    REVIEWERS
    Small Business28%
    Midsize Enterprise19%
    Large Enterprise53%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise13%
    Large Enterprise70%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise16%
    Large Enterprise64%
    Buyer's Guide
    Azure Data Factory vs. FME
    March 2024
    Find out what your peers are saying about Azure Data Factory vs. FME and other solutions. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    Azure Data Factory is ranked 1st in Data Integration with 79 reviews while FME is ranked 23rd in Data Integration with 5 reviews. Azure Data Factory is rated 8.0, while FME is rated 8.2. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of FME writes "Great for handling large volumes of data, but it is priced a bit high". Azure Data Factory is most compared with Informatica PowerCenter, Alteryx Designer, Informatica Cloud Data Integration, Snowflake and Microsoft Azure Synapse Analytics, whereas FME is most compared with Alteryx Designer, Talend Open Studio, SSIS, Informatica PowerCenter and SAP Data Services. See our Azure Data Factory vs. FME report.

    See our list of best Data Integration vendors.

    We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.