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."Allows more data between on-premises and cloud solutions"
"The trigger scheduling options are decently robust."
"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."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."
"Data Factory's best features are simplicity and flexibility."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"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 standard plug-ins available for different data sources."
"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."
"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."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"There aren't many third-party extensions or plugins available in the solution."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"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."
"The speed and performance need to be improved."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"There's space for improvement in the development process of the data pipelines."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"Improvements could be made to mapping presentations."
"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."
"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."
"To get a higher rating, it would have to improve the price and the associated scalability. These are the main issues."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while FME is ranked 25th in Data Integration with 5 reviews. Azure Data Factory is rated 8.0, while FME is rated 8.6. 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, Informatica Cloud Data Integration, Alteryx Designer, 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.
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