Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."

"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."

"We have found the bulk load feature very valuable."

"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."

"The trigger scheduling options are decently robust."

"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."

"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."

"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."

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

"The setup and configuration process could be simplified."

"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 pricing model should be more transparent and available online."

"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."

"It does not appear to be as rich as other ETL tools. It has very limited capabilities."

"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."

"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."

"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."

"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."

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

"I don't see a cost; it appears to be included in general support."

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

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"Pricing appears to be reasonable in my opinion."

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

"I would not say that this product is overly expensive."

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

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