A stock-trading application requires sub-millisecond latency for processing trade requests. Trading data is stored in DynamoDB, but load testing shows data retrieval is slower than required. Which solution will reduce retrieval latency with minimal effort?

Using DynamoDB Accelerator (DAX) is the most effective solution for reducing retrieval latency to sub-millisecond levels with minimal effort. DAX is a fully managed, highly available, in-memory cache specifically designed for DynamoDB. It transparently caches frequently accessed data, significantly speeding up read-heavy workloads without requiring application code changes. Adding local secondary indexes (LSIs) would improve query flexibility but not necessarily reduce retrieval latency for existing queries, and it requires schema changes. Moving data to Amazon S3 is unsuitable as S3 is an object storage service not designed for sub-millisecond, transactional data retrieval like DynamoDB. S3 Transfer Acceleration optimizes uploads, not retrieval latency for application data. Adding retries with exponential backoff improves fault tolerance but does not reduce the initial retrieval latency; it only helps in cases of transient errors.