Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."

"Azure Data Factory became more user-friendly when data-flows were introduced."

"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."

"We use the solution to move data from on-premises to the cloud."

"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."

"It is a complete ETL Solution."

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

"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."

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

"Currently, smaller businesses face a disadvantage in terms of pricing, and reducing costs could address this issue."

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

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

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

"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."

"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."

"Data Factory's cost is too high."

"If the user interface was more user friendly and there was better error feedback, it would be helpful."

"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."

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."

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

"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."

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

"The pricing is a bit on the higher end."

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

"The solution's pricing is competitive."

"The solution is cheap."

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