Uber

Streaming Company of the Year

2023
Uber needed a reliable (>99.99%), fast (<10 ms), and scalable (10 T message a day) data processing and messaging platform to power daily business like rides, deliveries, operations, offline...
Uber relies on Apache Kafka for uninterrupted data flow and business continuity.

Uber used Kafka to process 10 T messages/day for fast, reliable, and real-time data processing and messaging for ride and delivery services, data ingestion, logging, change data capture, and pub/sub.

Data Streaming Technology Used:

Apache Kafka®

What problem were they looking to solve with Data Streaming Technology?

Uber needed a reliable (>99.99%), fast (<10 ms), and scalable (10 T message a day) data processing and messaging platform to power daily business like rides, deliveries, operations, offline data ML, analytics, etc.

How did they solve the problem?

Uber used Kafka to build a mission-critical data processing and messaging platform with innovations such as real-time exactly-once semantics, a consumer push proxy with strong failure resilience capability, automatic consumer rebalance, error handling, smart message routing, built-in retry and dead-letter queue (DLQ) for poison pill messages, simplified gRPC interfaces, intelligent user group management, reliable and fast cross-DC replication, tiering, and security.

What was the positive outcome? 

Uber relies on Apache Kafka for uninterrupted data flow and business continuity. Using Kafka's messaging platform, Uber has achieved faster, reliable data processing, enabling real-time decisions and dynamic pricing. Communication between passengers and drivers improved with timely updates. Uber has gained valuable insights from data analysis, optimizing operations, and enhancing the user experience. These outcomes have boosted efficiency, customer satisfaction, and Uber's market competitiveness.

Additional Links: