Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

"We have been using drivers to connect to various data sets and consume data."

"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."

"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."

"It is a complete ETL Solution."

"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."

"Its integrability with the rest of the activities on Azure is most valuable."

"Data Factory's most valuable feature is Copy Activity."

"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."

"The drag-and-drop functionality makes it easy for business users."

"The number of standard adaptors could be extended further."

"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."

"The inability to connect local VMs and local servers into the data flow is a limitation that prevents giving Azure Data Factory a perfect score."

"In the next release, it's important that some sort of scheduler for running tasks is added."

"The pricing scheme is very complex and difficult to understand."

"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."

"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."

"Lacks a decent UI that would give us a view of the kinds of requests that come in."

"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."

"Pricing appears to be reasonable in my opinion."

"This is a cost-effective solution."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

"ADF is cheaper compared to AWS."

"Product is priced at the market standard."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

"The pricing model is based on usage and is not cheap."

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."

"The open-source version is free to use, although it has a limitation of two-million records."