This document discusses Uber's use of stream processing for their marketplace. It outlines several key use cases including real-time OLAP, complex event processing, and supply positioning. It then describes the challenges of processing large-scale geo-spatial temporal data in near real-time. The document proposes an overall architecture using Apache Kafka for event collection and Apache Samza for event processing. It notes some of the applications that can be built including dashboards, ad-hoc queries, and data visualizations. Finally, it discusses some trade-offs around using Lambda vs Kappa architectures and limitations of Samza.