Every day, more than 18M riders key their location and destination into the Uber mobile app to request a ride or a meal. Unbeknownst to them, each transaction is plugged into complex algorithms built on insight gleaned from petabytes of data. The results come back in seconds with the most optimal recommendations for nearby drivers and pricing based on supply and demand economics.
Data and analytics drive Uber to growth, profitability, and expansion into new business areas. To power this mammoth analytical undertaking, Uber chose the open-source Presto distributed query engine.
In this case study you’ll learn why Uber chose Presto and how they’re using the open source SQL query engine to run mission-critical analytics to power many of their analytical use cases.