Question 23 of 1,663
DBS-C01 Workload-Specific Database Design Practice Question
A media company is storing large video files (up to 10 GB each) in Amazon S3 and needs to maintain metadata about each file, including title, duration, and upload timestamp. The workload involves frequent writes (1000+ per second) and occasional read queries by title. Which database is best suited for this metadata store?
⚠ Common exam trap
AWS often tests the misconception that a relational database (RDS) is always the default for metadata, but the high write throughput and simple query pattern here make DynamoDB the correct choice, not RDS.
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
Amazon DynamoDB is the best choice because it supports single-digit millisecond latency at any scale, handles over 1000 writes per second with auto-scaling, and can efficiently serve occasional read queries by title using a global secondary index (GSI) on the title attribute. Its fully managed, serverless nature eliminates operational overhead for high-throughput metadata storage.
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 Neptune
Why it's wrong here
Neptune is designed for graph relationships, not simple metadata storage.
- ✗
Amazon RDS for MySQL
Why it's wrong here
RDS may struggle with 1000+ writes per second without extensive scaling.
- ✓
Amazon DynamoDB
Why this is correct
DynamoDB supports high write throughput and fast queries by partition key.
- ✗
Amazon ElastiCache for Memcached
Why it's wrong here
ElastiCache for Memcached is an in-memory key-value store that lacks native persistence, so any metadata written would be lost on node failure or restart, making it unsuitable for durable storage of video file metadata. It is tempting because its sub-millisecond latency and support for high write throughput (1000+ writes per second) would excel as a caching layer for read-heavy workloads, where data can be regenerated from a persistent source.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Last reviewed: Jun 30, 2026
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.
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