A company installed smart meters at customer sites that record power usage every minute and send readings to a remote endpoint. The company needs an endpoint to receive readings and store them in a database. They must record location ID and timestamp and offer customers low-latency access to current and historical usage on demand. Demand will grow substantially and the solution should scale without downtime and be cost-effective. Which storage solution best meets these requirements?

DynamoDB is ideal for this use case due to its high scalability, low-latency access, and cost-effectiveness for high-volume, real-time data ingestion and retrieval. A composite primary key with location ID as the partition key and timestamp as the sort key allows efficient querying of all readings for a specific location, or readings within a time range for a specific location, directly addressing the requirement for on-demand access to current and historical usage. Amazon RDS, while relational, struggles with the scale and low-latency requirements of minute-by-minute data from numerous devices. ElastiCache for Redis is an in-memory cache, not a primary persistent data store, and would be too expensive for storing all historical data. Amazon S3 with Athena is suitable for large-scale analytics but does not provide the low-latency, real-time access needed for individual customer usage queries.