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Workload-Specific Database DesignmediumMultiple ChoiceObjective-mapped

DBS-C01 Workload-Specific Database Design Practice Question

A company is designing a database for an IoT application that ingests millions of sensor readings per second. Each reading is a small JSON document (less than 1 KB) and must be stored with low latency. Queries are primarily by device ID and timestamp range. The team expects to rarely update or delete old data. Which AWS database solution is MOST cost-effective and performant?

⚠ Common exam trap

The DBS-C01 exam often tests the misconception that S3 is suitable for low-latency, high-write IoT ingestion, but the trap here is that S3's eventual consistency and higher per-request latency make it inappropriate for real-time sensor data storage, whereas DynamoDB's design for exactly this pattern is the correct choice.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Amazon DynamoDB with a composite primary key (device_id, timestamp)

Amazon DynamoDB with a composite primary key (device_id, timestamp) is the most cost-effective and performant solution because it provides single-digit millisecond latency for point lookups and range queries, scales horizontally to handle millions of writes per second, and its on-demand or auto-scaling capacity model avoids over-provisioning. The access pattern of querying by device ID and timestamp range maps directly to DynamoDB's partition and sort key design, enabling efficient use of the Query API without scanning.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Amazon S3 with a partition prefix of device_id/timestamp/

    Why it's wrong here

    S3 has eventual consistency and higher latency per PUT; not ideal for high-rate small writes.

  • Amazon Redshift with distribution key on device_id

    Why it's wrong here

    Redshift is built for analytical queries on large datasets, not for real-time point writes.

  • Amazon DynamoDB with a composite primary key (device_id, timestamp)

    Why this is correct

    DynamoDB provides low-latency, high-throughput ingestion and efficient querying by device and time.

  • Amazon RDS for MySQL with multiple read replicas

    Why it's wrong here

    RDS is relational and not optimized for high-velocity ingestion of small documents; scaling is limited.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This DBS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DBS-C01 exam.