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."It makes it easy to collect data from different sources."
"Data Factory's best features are simplicity and flexibility."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"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."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"The solution can scale very easily."
"It is beneficial that the solution is written with Spark as the back end."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"The drag-and-drop functionality makes it easy for business users."
"When working with AWS, we have noticed that the difference between ADF and AWS is that AWS is more customer-focused. They're more responsive compared to any other company. ADF is not as good as AWS, but it should be. If AWS is ten out of ten, ADF is around eight out of ten. I think AWS is easier to understand from the GUI perspective compared to ADF."
"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."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"There is no built-in pipeline exit activity when encountering an error."
"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"When the record fails, it's tough to identify and log."
"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."
More Infogix Data360 Analyze [EOL] Pricing and Cost Advice →
Earn 20 points
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.
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.
