Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

"The solution can scale very easily."

"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."

"The data copy template is a valuable feature."

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."

"The most valuable feature is the ease in which you can create an ETL pipeline."

"The best part of this product is the extraction, transformation, and load."

"It's extremely consistent."

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

"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."

"There's space for improvement in the development process of the data pipelines."

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

"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."

"The main challenge with implementing Azure Data Factory is that it processes data in batches, not near real-time. To achieve near real-time processing, we need to schedule updates more frequently, which can be an issue. Its interface needs to be lighter."

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

"Some known bugs and issues with Azure Data Factory could be rectified."

"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."

"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."

"Product is priced at the market standard."

"Understanding the pricing model for Data Factory is quite complex."

"The price you pay is determined by how much you use it."

"Data Factory is affordable."

"The licensing is a pay-as-you-go model, where you pay for what you consume."

"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."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

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