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Amazon Redshift

Time-travel support​

Time-travel is not currently supported by DirectQuery for Redshift. This means that updating that applications based on this Database are subject to data desynchronization in case of changes in the Database.
Read this page to learn more about the visible effects of this desynchronization.

Vector supports​

Only multi-rows vectors and multi-columns vectors are supported by Redshift.

The array functions available in Redshift really use the SUPER data type. This data type can emulate a basic array type, but it does not offer powerful aggregation functions to work with them.

Gotchas​

Nullable fields​

Redshift can define fields with nullable types. DirectQuery is capable of detecting this and defines its internal model accordingly.
While this is not a problem in itself, it can conflict with the rule in Atoti cubes that all levels must be based on non-nullable values. This does not create an issue of any sort as the local model is updated behind the scene, assigning a default value based on the type.
It has a side effect on the query performance, as DirectQuery must convert on-the-fly null values to their assigned default values, as well as adding extra conditions during joins to handle null values on both sides.