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Post ProdigyUnsupported views for a KQL database
Hi,
reading the documentation it seems that a KQL view is not supported for a KQL database, while a materialized view is supported.
Which is the reason for this unsupported feature? Thanks
Hi pmscorca ,
This design choice is primarily due to the different purposes and performance characteristics of these two types of views. KQL Views are essentially virtual tables that do not store data physically. They are defined by a query and provide a way to simplify complex queries by encapsulating them. However, because they do not store data, every time you query a KQL view, the underlying query must be executed, which can be resource-intensive and slow, especially with large datasets or complex queries.
Materialized Views, on the other hand, store the result of the query physically. This means that querying a materialized view is much faster because the data is precomputed and stored. This is particularly useful for real-time analytics and scenarios where performance is critical. By supporting materialized views, Microsoft Fabric ensures that users can achieve high performance and efficiency in their data operations.
You can refer to the following documents that may be helpful to you:
Create a KQL database - Microsoft Fabric | Microsoft Learn
Query data in a KQL queryset - Microsoft Fabric | Microsoft Learn
Best Regards,
Neeko Tang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
1 Reply
Hi pmscorca ,
This design choice is primarily due to the different purposes and performance characteristics of these two types of views. KQL Views are essentially virtual tables that do not store data physically. They are defined by a query and provide a way to simplify complex queries by encapsulating them. However, because they do not store data, every time you query a KQL view, the underlying query must be executed, which can be resource-intensive and slow, especially with large datasets or complex queries.
Materialized Views, on the other hand, store the result of the query physically. This means that querying a materialized view is much faster because the data is precomputed and stored. This is particularly useful for real-time analytics and scenarios where performance is critical. By supporting materialized views, Microsoft Fabric ensures that users can achieve high performance and efficiency in their data operations.
You can refer to the following documents that may be helpful to you:
Create a KQL database - Microsoft Fabric | Microsoft Learn
Query data in a KQL queryset - Microsoft Fabric | Microsoft Learn
Best Regards,
Neeko Tang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.