In-Memory mode

The default in-memory mode is highly optimized for query performance and supports additional modeling and development flexibility with DAX functions. With compression, columnar storage, parallel query plans, and other techniques an import mode model is able to support a large amount of data (for example, 50M rows) and still perform well with complex analysis expressions. Multiple data sources can be accessed and integrated in a single data model and all DAX functions are supported for measures, columns, and role security.

However, the import or refresh process must be scheduled and this is currently limited to eight refreshes per day for datasets in shared capacity (48X per day in premium capacity). As an alternative to scheduled refreshes in the Power BI service, REST APIs can be used to trigger a data refresh of a published dataset. For example, an HTTP request to a Power BI REST API calling for the refresh of a dataset can be added to the end of a nightly update or ETL process script such that published Power BI content remains aligned with the source systems. More importantly, it's not currently possible to perform an incremental refresh such as the Current Year rows of a table (for example, a table partition) or only the source rows that have changed. In-Memory mode models must maintain a file size smaller than the current limits (1 GB compressed currently, 10GB expected for Premium capacities by October 2017) and must also manage refresh schedules in the Power BI Service. Both incremental data refresh and larger dataset sizes are identified as planned capabilities of the Microsoft Power BI Premium Whitepaper (May 2017).