How should the developer implement the cache to achieve the LOWEST latency?
Create an Amazon ElastiCache for Memcached instance. Serialize the data as JSON before caching the data.
Create an Amazon ElastiCache for Redis instance. Use a Redis client library to cache the data.
Create an Amazon DynamoDB table. Serialize the data as JSON before caching the data.
Create an Amazon ElastiCache for Memcached instance. Use a Memcached client library to cache the data.
Explanations:
While Memcached can be used for caching, it does not support data structures like sets and sorted sets natively. Using JSON serialization adds overhead and complexity, leading to higher latency compared to Redis.
Amazon ElastiCache for Redis supports sets and sorted sets natively, providing the necessary data structures for efficient caching. It also offers low latency and high performance, making it suitable for frequently queried data.
Amazon DynamoDB is a database service and not optimized for caching purposes. Although it can store JSON data, it does not provide the low-latency access that in-memory caches like Redis offer. Additionally, it does not natively support sets or sorted sets.
Similar to option A, Memcached does not support complex data structures like sets and sorted sets. While it can be used for simple key-value caching, it lacks the capabilities required for the specified use case, resulting in potentially higher latency.
Based on what I know, the answer is:
Create an Amazon ElastiCache for Redis instance. Use a Redis client library to cache the data.