Query acceleration for large datasets (Public Preview)

Note

These release notes describe functionality that may not have been released yet. To see when this functionality is planned to release, please review Summary of what’s new. Delivery timelines and projected functionality may change or may not ship (see Microsoft policy).

Users can create DirectQuery models over any size data in sources, such as Spark and Azure SQL Data Warehouse, and then accelerate common queries by building in-memory aggregations over some of the data. Common queries use the aggregated cache to return results in a fraction of a second instead of directly querying the source. Users can create datasets of massive size and still provide interactive querying.