This article discusses the drawbacks of eventual consistency in database systems, particularly for application developers and users. It highlights the confusion and bugs that arise from stale data when using read replicas and presents Aurora DSQL as a solution that ensures strong consistency for all reads.

The article details how Uber transitioned from static rate limiting to a more dynamic load management system to handle database overload effectively. It explores the architecture of Uber’s databases, the challenges faced, and the innovative solutions implemented, such as CoDel queues and the Scorecard engine, to ensure stability and fairness in a multitenant environment.