At Uber, real-time analytics allow us to attain business insights and operational efficiency, enabling us to make data-driven decisions to improve experiences on the Uber platform. For example, our operations team relies on data to monitor the market health and spot potential issues on our platform; software powered by machine learning models leverages data to predict rider supply and driver demand; and data scientists use data to improve machine learning models for better forecasting. In the past, we have utilized many third-party database solutions for real-time analytics, but none were able to simultaneously address all of our functional, scalability, performance, cost, and operational requirements.
Released in November 2018, AresDB is an open source, real-time analytics engine that leverages an unconventional power source, graphics processing units (GPUs), to enable our analytics to grow at scale. An emerging tool for real-time analytics, GPU technology has advanced significantly over the years, making it a perfect fit for real-time computation and data processing in parallel. In the following sections, we describe the design of AresDB and how this powerful solution for real-time analytics has allowed us to more performatively and efficiently unify, simplify, and improve Uber’s real-time analytics database solutions.
After reading this article, we hope you try out AresDB for your own projects and find the tool useful your own analytics needs, too!
Source: uber.com