The Parallel Data Warehouse (PDW) officially supports Analysis Services as a data source, both the Multidimensional model (ROLAP and MOLAP modes) and the Tabular model (In-Memory and DirectQuery modes). The big benefit of using ROLAP or DirectQuery is you get real-time query access to the relational data source in PDW and don’t have to process the cube. You create MDX queries when using ROLAP, which get translated to SQL when hitting PDW, and you create DAX queries when using DirectQuery, which also get translated to SQL when hitting PDW.
An SSAS cube that uses PDW as a data source is just like any other data source that SSAS uses. Performance is usually fast because of the clustered columnstore indexes, with the only caveat is sometimes the SQL that is generated by DirectQuery to pull data from PDW is not that great (the SQL generated by ROLAP is usually pretty good).
The other thing to note about DirectQuery, which applies to any data source, is you can’t use PerformancePoint or Excel PivotTables with DirectQuery. This is because MDX queries are not supported for a tabular model in DirectQuery mode, only DAX, so you need to use a DAX client like Power View (PerformancePoint and Excel PivotTables generate MDX queries behind the scenes). The other limitation with DirectQuery is it does not cache results like ROLAP. Finally, there are some DAX functions that are not supported in DirectQuery mode and some that might return different results (see Formula Compatibility in DirectQuery Mode). So it seems that ROLAP is the better choice over DirectQuery for many situations.
One limit of ROLAP to note is it does not support parent-child hierarchies. One improvement is Distinct Count performance for ROLAP queries is faster if you enable an optimization.