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.
I give the scalability an eight out of ten, indicating it scales well for our needs.
The solution has a high level of stability, roughly a nine out of ten.
Microsoft Parallel Data Warehouse is stable for us because it is built on SQL Server.
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.
When there are many users or many expensive queries, it can be very slow.
Microsoft Parallel Data Warehouse is excellent but very expensive.
The ETL designing process could be optimized for better efficiency.
The pricing is cost-effective.
It is considered cost-effective.
Microsoft Parallel Data Warehouse is very expensive.
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 columnstore index enhances data query performance by using less space and achieving faster performance than general indexing.
Microsoft Parallel Data Warehouse is used in the logistics area for optimizing SQL queries related to the loading and unloading of trucks.
The interface is very user-friendly.
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.
The traditional structured relational data warehouse was never designed to handle the volume of exponential data growth, the variety of semi-structured and unstructured data types, or the velocity of real time data processing. Microsoft's SQL Server data warehouse solution integrates your traditional data warehouse with non-relational data and it can handle data of all sizes and types, with real-time performance.
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