Which solution will meet these requirements MOST cost-effectively?
Store the smart meter readings in an Amazon RDS database. Create an index on the location ID and timestamp columns. Use the columns to filter on the customers’ data.
Store the smart meter readings in an Amazon DynamoDB table. Create a composite key by using the location ID and timestamp columns. Use the columns to filter on the customers’ data.
Store the smart meter readings in Amazon ElastiCache for Redis. Create a SortedSet key by using the location ID and timestamp columns. Use the columns to filter on the customers’ data.
Store the smart meter readings in Amazon S3. Partition the data by using the location ID and timestamp columns. Use Amazon Athena to filter on the customers’ data.
Explanations:
Amazon RDS is a relational database that can handle structured data but may struggle with high write throughput at one-minute intervals for a large number of customers. Indexing can improve query performance, but it may also introduce overhead, impacting performance under heavy load and making scaling challenging without downtime.
Amazon DynamoDB is a NoSQL database designed for high availability and scalability, making it suitable for handling the high-frequency updates from smart meters. A composite primary key using location ID and timestamp allows for efficient querying and retrieval of data without impacting performance, even with increased demand.
Amazon ElastiCache for Redis is primarily an in-memory caching service that excels in low-latency data access but is not ideal for persistent storage of time-series data like smart meter readings. While it can support high throughput, the risk of data loss and complexity in managing persistence makes it less suitable for the use case.
Storing data in Amazon S3 with partitioning and querying through Amazon Athena is a cost-effective option for large datasets but may introduce higher latency for real-time access compared to a database solution. It is more suitable for batch processing and analytics rather than low-latency access, which is a primary requirement here.
I draft that the answer is:
Store the smart meter readings in an Amazon DynamoDB table. Create a composite key by using the location ID and timestamp columns. Use the columns to filter on the customers’ data.
I evaluate that the answer is:
Store the smart meter readings in an Amazon DynamoDB table. Create a composite key by using the location ID and timestamp columns. Use the columns to filter on the customers’ data.