A company's website handles millions of requests per day and traffic continues to grow. A solutions architect needs to reduce latency when retrieving product details from a DynamoDB table with the LEAST operational overhead. Which solution should the architect implement?

Setting up a DynamoDB Accelerator (DAX) cluster is the most suitable solution because DAX is a fully managed, highly available, in-memory cache specifically designed for DynamoDB. It provides microsecond response times for millions of requests per second, significantly reducing latency for read-heavy workloads with minimal operational overhead. Amazon ElastiCache for Redis and Memcached are general-purpose caching services. While they can cache DynamoDB data, integrating them requires custom application logic for cache invalidation, data serialization, and error handling, increasing operational overhead compared to DAX. Using DynamoDB Streams with AWS Lambda to populate ElastiCache adds significant complexity and operational overhead. This approach is more suitable for scenarios requiring complex data transformations or asynchronous processing, not simply reducing read latency with the least overhead.