An application stores data in Amazon DynamoDB and currently processes it in a nightly batch. Analysts want processed results available in near-real time as data arrives. Which architectural pattern allows processing data as it is received?

The event-driven architectural pattern is correct because it allows systems to react to changes (events) as they occur. In this scenario, new data arriving in DynamoDB can trigger an event (e.g., via DynamoDB Streams), which then initiates immediate processing. This enables near-real-time analytics, fulfilling the requirement. Client-server driven describes a basic interaction model but doesn't inherently imply real-time processing of data arrivals. Fan-out driven refers to distributing a single message to multiple consumers, which can be part of an event-driven system but isn't the overarching pattern for real-time data processing. Schedule-driven implies processing at fixed intervals, which is the current nightly batch approach and does not meet the near-real-time requirement.