A company is building an application for stock trading. The application needs sub-millisecond latency for processing trade requests. The company uses Amazon DynamoDB to store all the trading data that is used to process each trading request.
A development team performs load testing on the application and finds that the data retrieval time is higher than expected. The development team needs a solution that reduces the data retrieval time with the least possible effort.
Which solution meets these requirements?
A. Add local secondary indexes (LSIs) for the trading data.
B. Store the trading data in Amazon S3, and use S3 Transfer Acceleration.
C. Add retries with exponential backoff for DynamoDB queries.
D. Use DynamoDB Accelerator (DAX) to cache the trading data.
A development team performs load testing on the application and finds that the data retrieval time is higher than expected. The development team needs a solution that reduces the data retrieval time with the least possible effort.
Which solution meets these requirements?
A. Add local secondary indexes (LSIs) for the trading data.
B. Store the trading data in Amazon S3, and use S3 Transfer Acceleration.
C. Add retries with exponential backoff for DynamoDB queries.
D. Use DynamoDB Accelerator (DAX) to cache the trading data.