Azure Data Factory vs Microsoft Analytics Platform System comparison

"I like the basic features like the data-based pipelines."

"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."

"It's extremely consistent."

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

"The most valuable features are data transformations."

"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."

"The data flows were beneficial, allowing us to perform multiple transformations."

"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."

"Microsoft Analytics Platform System's most valuable feature is its ecosystems and seamless integration with other Microsoft reporting platforms and databases."

"This is a well-integrated solution and that integration empowers results."

"I like that it's integrated with other Azure products."

"The Cube Solution is quite different when compared to the rest of the competition and has unique functionality for advanced analytics."

"Helps our customers to discover trends, which provides useful information based on their business."

"We leverage its capabilities for many applications. We can integrate with our databases, like Oracle, MySQL, or any other, using Microsoft Integration Services."

"It is closely integrated with other products in the MS portfolio."

"This solution will connect to any database, you can combine databases, and you can create a cube or tabular model."

"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."

"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."

"Some of the optimization techniques are not scalable."

"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."

"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."

"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."

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

"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."

"The flexibility of this solution needs to be improved because you cannot make changes at every one of the different steps."

"Functionality needs to be more up-to-date with competing products."

"We need better real-time analytics capabilities. It's a bit challenging for us."

"Microsoft Analytics Platform System could have better support."

"The pricing model needs to be improved."

"I think the biggest problem with the product is that it does a data ingest model, which is very expensive."

"​Hybrid environments are complex to manage."

"Releases of new products and functionality is never accompanied by associated documentation, training and resources that adequately explain the release."

"Data Factory is expensive."

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

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

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

"The price you pay is determined by how much you use it."

"The price is fair."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

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

"The initial price is lower than Oracle, but extensive use of SQL may lead to a higher total cost of ownership."

"Users have to pay extra for premium-level technical support."

"We are currently paying $200,000 a year for all the different parts of the suite during an ingest model Microsoft now charges us $700,000 a year."

"I rate Microsoft Analytics Platform System a seven out of ten for pricing."