273 results for "pinot" across all locations

We are piloting the introduction of estimated earnings per active hour on trip requests in a few cities in Chile, Argentina, and Mexico.

When choosing to accept a trip request, drivers consider many factors such as fare, distance, and time. Estimated earnings per kilometer is a simple way to compare trips requests that you receive.

We are piloting the introduction of estimated earnings per active hour on trip requests in a few cities in Chile, Argentina, Mexico, and USA.

When choosing to accept a trip request, drivers consider many factors such as fare, distance, and time. Estimated earnings per active hour is a simple way to compare trips requests that you receive.

Learn how Uber uses Apache Pinot for serving over 100 low-latency offline analytics use cases.

We engineered full SQL support on Apache Pinot to enable quick analysis and reporting on aggregated data, leading to improved experiences on our platform.

Uber has a complex marketplace consisting of riders, drivers, eaters, restaurants and so on. Operating that marketplace at a global scale requires real-time intelligence and decision making.

At Uber, we serve 500 million Pinot queries every day. Learn how we optimized and built an internal fork of Presto to support query features like window functions and sub-queries, all while supporting sub-second latencies at thousands of QPS.

With contributions from Uber and others, Apache Pinot™ now supports deletion with upsert tables! Learn how Uber drove these advancements and how you can benefit from cost-efficient infinite retention.

Updating enterprise-scale software and infrastructure without creating unintentional downstream issues is a daunting task–we leveraged Apache Pinot to create Healthline, a tool for minimizing release errors in real time and at Uber scale.

Have more rows than you can count on two hands? Don’t feel like using approximations? Learn how Uber uses Apache Pinot™ to count!