Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
The technical support for Azure Data Factory is generally acceptable.
Azure Data Factory is highly scalable.
Most of our functions or jobs are queued due to that.
The solution has a high level of stability, roughly a nine out of ten.
I have faced stability issues, mainly due to the storage my organization has, though I am not sure if it's specifically due to the tool.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
There is a problem with the integration with third-party solutions, particularly with SAP.
The pricing is cost-effective.
It is considered cost-effective.
It connects to different sources out-of-the-box, making integration much easier.
The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with.
I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets.
The product is not complex; I do not have to create stored procedures, functions, or views.
Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.
VMware Tanzu is a robust platform tailored for data warehousing, complex analytics, BI applications, and predictive analytics. It excels in scalability, performance, and parallel processing, enhancing data handling efficiency. Users report significant productivity improvements and streamlined operations, making it ideal for comprehensive data solutions.
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