A company has a web application for travel ticketing. The application is based on a database that runs in a single data center in North America. The company wants to expand the application to serve a global user base. The company needs to deploy the application to multiple AWS Regions. Average latency must be less than 1 second on updates to the reservation database. The company wants to have separate deployments of its web platform across multiple Regions. However, the company must maintain a single primary reservation database that is globally consistent. Which solution should a solutions architect recommend to meet these requirements?

The correct solution is to convert the application to use Amazon DynamoDB with a global table. DynamoDB Global Tables provide a fully managed, multi-Region, multi-active database that delivers fast, local read and write performance with single-digit millisecond latency. This directly addresses the requirement for average latency less than 1 second on updates to a globally consistent primary reservation database across multiple AWS Regions. Each Regional deployment can use its local DynamoDB endpoint for optimal performance. Migrating to Amazon Aurora MySQL with Read Replicas (option B) or Amazon RDS for MySQL with Read Replicas (option C) would not meet the requirement for sub-1-second update latency across Regions for a single primary database. Read replicas are eventually consistent and primarily for read scaling, not for low-latency, globally consistent writes to a single logical database across multiple active Regions. Migrating to Amazon Aurora Serverless with Lambda synchronization (option D) introduces significant complexity and potential for higher latency and eventual consistency issues due to manual synchronization via Lambda functions, which would likely exceed the 1-second update latency requirement for a globally consistent database.