Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

"I like that it's a monolithic data platform. This is why we propose these solutions."

"The flexibility that Azure Data Factory offers is great."

"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."

"The most valuable features are data transformations."

"I can do everything I want with SSIS and Azure Data Factory."

"The most valuable feature of this solution would be ease of use."

"The solution handles large volumes of data very well. One of its best features is its ability to integrate data end-to-end, from pulling data from the source to accessing Databricks. This makes it quite useful for our needs."

"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."

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

"There is a problem with the integration with third-party solutions, particularly with SAP."

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

"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."

"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."

"The thing we missed most was data update, but this is now available as of two weeks ago."

"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."

"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."

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

"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."

"The cost is based on the amount of data sets that we are ingesting."

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

"I would rate Data Factory's pricing nine out of ten."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

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

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

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"Data Factory is affordable."

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