Real-time data (# of ride requests, # of drivers available, weather, game) enables operations teams to make informed decisions like surge pricing , maximum dispatch ETA calculating, and demand/supply forecasting about our services that improve user experiences on the Uber platform. While batched data can provide powerful insights by identifying medium-term and long-term trends, Uber services can combine streaming data with real-time processing to create actionable insights on a minute-by-minute basis.
We built Gairos, Uber’s real-time data processing, storage, and querying platform to facilitate streamlined and efficient data exploration at scale . It empowers teams to better understand and improve the efficiency of the Uber Marketplace through data intelligence. Use cases include surge pricing , maximum dispatch ETA calculating, and demand/supply forecasting.
To ensure that Gairos can continue to optimize its performance across an ever-expanding portfolio of use cases, we re-architectured the platform for greater scalability, stability and sustainability. Two of these optimization strategies with the greatest impact include data-driven sharding and query routing and intelligent caching.