A new class of modern transactions has emerged, driven by IoT sensor information, website traffic logs, and global financial reporting, which require real-time data warehouses to handle the volume and velocity of data. These warehouses need to ingest and persist data in real time while serving low-latency analytic queries to a large number of simultaneous users. Incorporating machine learning capabilities into these warehouses can simplify data architectures and provide access to real-time information for faster critical decisions, enabling organizations to harness insights from vast arrays of live inputs.