We performed a comparison between Azure Data Factory and Infogix Data360 Analyze [EOL] based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."The most valuable aspect is the copy capability."
"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."
"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"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."
"The solution has a good interface and the integration with GitHub is very useful."
"We have been using drivers to connect to various data sets and consume data."
"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."
"The trigger scheduling options are decently robust."
"The drag-and-drop functionality makes it easy for business users."
"There is no built-in pipeline exit activity when encountering an error."
"When the record fails, it's tough to identify and log."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"Data Factory's performance during heavy data processing isn't great."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"The pricing scheme is very complex and difficult to understand."
"The memory processing needs to be improved because when you deal with a large amount of data, the interface tends to hang a little bit."
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Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Infogix Data360 Analyze [EOL] is ranked 52nd in Data Integration. Azure Data Factory is rated 8.0, while Infogix Data360 Analyze [EOL] is rated 7.0. 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 Infogix Data360 Analyze [EOL] writes "Easy drag-and-drop interface and supports custom Python functions, but the performance needs to be better". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas Infogix Data360 Analyze [EOL] is most compared with Alteryx Designer and Informatica PowerCenter.
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