A company is developing a mobile game that streams score updates to a backend processor and then posts results to a leaderboard. The solution must handle large traffic spikes, process updates in the order received, store processed updates in a highly available database, and minimize management overhead. What should the solutions architect implement?

This solution effectively addresses all requirements. Amazon Kinesis Data Streams handles large traffic spikes and ensures updates are processed in order. AWS Lambda provides a serverless, scalable way to process the stream data, minimizing management overhead. Amazon DynamoDB is a highly available, scalable NoSQL database ideal for storing processed updates with low latency. Incorrect options: Using EC2 instances for processing introduces management overhead compared to Lambda. Amazon Redshift is an analytical data warehouse, not ideal for real-time transactional updates. Amazon SNS is a pub/sub messaging service, not designed for ordered processing of a stream of data. A SQL database on EC2 requires significant management overhead. Amazon SQS is a message queue, but Kinesis Data Streams is better suited for ordered processing of a continuous stream of data. EC2 instances again add management overhead, and Amazon RDS, while highly available, might not offer the same low-latency, high-scale performance as DynamoDB for this specific use case.