DVA-C02 · Question #82
A company has installed smart meters in all its customer locations. The smart meters measure power usage at 1-minute intervals and send the usage readings to a remote endpoint for collection. The comp
The correct answer is B. Store the smart meter readings in an Amazon DynamoDB table. Create a composite key by using. Amazon DynamoDB provides single-digit millisecond latency, automatic scaling without downtime, and a composite primary key model that is ideal for time-series IoT data indexed by location and timestamp.
Question
A company has installed smart meters in all its customer locations. The smart meters measure power usage at 1-minute intervals and send the usage readings to a remote endpoint for collection. The company needs to create an endpoint that will receive the smart meter readings and store the readings in a database. The company wants to store the location ID and timestamp information. The company wants to give its customers low-latency access to their current usage and historical usage on demand. The company expects demand to increase significantly. The solution must not impact performance or include downtime while scaling. Which solution will meet these requirements MOST cost-effectively?
Options
- AStore the smart meter readings in an Amazon RDS database. Create an index on the location ID
- BStore the smart meter readings in an Amazon DynamoDB table. Create a composite key by using
- CStore the smart meter readings in Amazon ElastiCache for Redis. Create a SortedSet key by
- DStore the smart meter readings in Amazon S3. Partition the data by using the location ID and
How the community answered
(36 responses)- A11% (4)
- B56% (20)
- C6% (2)
- D28% (10)
Why each option
Amazon DynamoDB provides single-digit millisecond latency, automatic scaling without downtime, and a composite primary key model that is ideal for time-series IoT data indexed by location and timestamp.
Amazon RDS requires manual or scheduled scaling events, which can involve downtime, and does not scale transparently under sudden demand increases as well as DynamoDB.
DynamoDB's composite key (partition key = location ID, sort key = timestamp) enables highly efficient queries for both current and historical readings per location. DynamoDB scales horizontally and automatically to handle unpredictable demand spikes with no downtime, no performance degradation, and a pay-per-request pricing option that minimizes cost.
ElastiCache for Redis is an in-memory cache with limited persistence and storage capacity; it is not designed as a primary database for petabyte-scale historical time-series data.
Amazon S3 is optimized for object storage and batch analytics, not low-latency on-demand query access to individual readings needed for customer-facing dashboards.
Concept tested: DynamoDB composite key for IoT time-series data
Source: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.CoreComponents.html
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