Azure Data Factory vs Rivery comparison

"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 function of the solution is great."

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

"The most valuable aspect is the copy capability."

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

"It's extremely consistent."

"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."

"The solution's most valuable features are that it is quick to connect and simple to use."

"Connects to many APIs in the market and new ones are being added all the time."

"Azure Data Factory uses many resources and has issues with parallel workflows."

"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 has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."

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

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

"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."

"It would be better if it had machine learning capabilities."

"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."

"Lineage and an impact analysis or logic dependency are lacking."

"Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better."

"Product is priced at the market standard."

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

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

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

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

"Pricing appears to be reasonable in my opinion."

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

"The solution is cheap."

"I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten."