DBS-C01 Workload-Specific Database Design Practice Question
A company uses Amazon DynamoDB to store application logs. The logs have a TTL of 7 days. The operations team needs to run ad-hoc analytical queries on logs older than 7 days, which are automatically deleted by TTL. Which solution should the team implement to retain and analyze old logs?
⚠ Common exam trap
Many exam-takers think AWS Glue can directly query DynamoDB for historical analysis, but Glue is an ETL service that crawls existing data, not a query engine for deleted items, and TTL-deleted logs are permanently removed from DynamoDB.
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
✓
Use DynamoDB Streams to export logs to Amazon S3 and query with Amazon Athena.
DynamoDB Streams can capture item deletions (including TTL-based deletions) and export them to Amazon S3. Once the logs are in S3, Amazon Athena can run ad-hoc SQL queries directly on the data, providing a cost-effective and serverless analytical solution for logs older than 7 days.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use DynamoDB Streams to export logs to Amazon S3 and query with Amazon Athena.
Why this is correct
Streams capture data before deletion, and Athena can query S3 data cost-effectively.
- ✗
Disable TTL and use a scheduled Lambda function to archive logs to Amazon S3.
Why it's wrong here
Disabling TTL would cause uncontrolled growth.
- ✗
Increase the TTL to 30 days and query the logs directly in DynamoDB.
Why it's wrong here
Keeping logs in DynamoDB for 30 days is expensive for analytics.
- ✗
Use AWS Glue to crawl DynamoDB tables and create a data catalog for Athena queries.
Why it's wrong here
Glue can crawl DynamoDB but queries would still read from DynamoDB, incurring read costs.
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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