Azure Data Factory vs Palantir Gotham comparison

"From what we have seen so far, the solution seems very stable."

"The data copy template is a valuable feature."

"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."

"It is easy to integrate."

"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."

"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."

"It is easy to deploy workflows and schedule jobs."

"It is a complete ETL Solution."

"This solution is seamless. From one platform, we can do just about anything."

"The user interface could use improvement. It's not a major issue but it's something that can be improved."

"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."

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

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

"Some prebuilt data source or data connection aspects are generic."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"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."

"The solution needs to be more connectable to its own services."

"I think there should be less coding involved. Currently, using it involves a tremendous amount of coding."

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

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

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

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

"ADF is cheaper compared to AWS."

"The solution's pricing is competitive."

"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."