Azure Data Factory vs Microsoft Analytics Platform System comparison

"I am one hundred percent happy with the stability."

"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."

"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."

"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."

"The trigger scheduling options are decently robust."

"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."

"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."

"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."

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

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

"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."

"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."

"I do not have any notes for improvement."

"There are performance issues, particularly with the underlying compute, which should be configurable."

"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."

"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."

"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."

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

"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."

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

"The pricing model needs to be improved."

"​Hybrid environments are complex to manage."

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

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

"Microsoft Analytics Platform System could have better support."

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

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

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

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

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

"The cost is based on the amount of data sets that we are ingesting."

"Data Factory is expensive."

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

"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."

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

"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."