Such languages offload more work onto the data model than SQL does.[0] For example, in the Tabular model (where you would use DAX), relationships are defined in

Such languages offload more work onto the data model than SQL does.[0] For example, in the Tabular model (where you would use DAX), relationships are defined in the model (and supported by an in-memory data structure that you can shortcut-think of as a pre-computed hash-join) and implicit in (most) expressions you write. If you think of SQL as a general-purpose query language, these BI-centric languages are DSLs for analytical queries. They are most useful for workloads where you have many queries that all use the same data model and are reasonably served by a pre-defined set of calculations/metrics. [0] Do not mistake me, good data modeling is important for SQL as well.