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 features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"In terms of my personal experience, it works fine."
"The most valuable feature of this solution would be ease of use."
"The scalability of the product is impressive."
"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."
"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"The drag-and-drop functionality makes it easy for business users."
"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."
"Data Factory's cost is too high."
"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."
"The user interface could use improvement. It's not a major issue but it's something that can 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 no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."
"Azure Data Factory's pricing in terms of utilization could be improved."
"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."
"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] doesn't meet the minimum requirements to be ranked 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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