Modern cars produce data. Lots of data. And Formula 1 cars produce more than their share. I will present a working demonstration of how modern data streaming can be applied to the data acquisition and analysis problem posed by modern motorsports. Instead of bringing multiple Formula 1 cars to the talk, I will show how we instrumented a high fidelity physics-based automotive simulator to produce realistic data from simulated cars running on the Spa-Francorchamps track. We move data from the cars, to the pits, to the engineers back at HQ. The result is near real-time visualization and comparison of performance and a great exposition of how to move data using messaging systems like Kafka, and process data in real time with Apache Spark, then analyse data using SQL with Apache Drill. The code from this talk will be made available as open source. Tugdual Grall is a Technical Evangelist at MapR, an open source advocate and a passionate developer. He currently works with the European developer communities to ease MapR, Hadoop and NoSQL adoption. Before joining MapR, Tug was Technical Evangelist at MongoDB and Couchbase. Tug has also worked as CTO at eXo Plaform and JavaEE product manager, and software engineer at Oracle. Tugdual is Co-Founder of the Nantes JUG (Java User Group) that holds since 2008 monthly meeting about Java ecosystem. Tugdual also writes a blog available at http://tgrall.github.io/ [LFC-8783]