DBS-C01 Workload-Specific Database Design Practice Question
A company runs a MySQL database on Amazon RDS. They need to export a subset of data to Amazon S3 for analysis using Amazon Athena. The data is stored in multiple tables with complex joins. What is the MOST efficient way to export the data?
⚠ Common exam trap
Candidates often confuse the AWS Schema Conversion Tool (SCT) as a data extraction tool, when it is actually designed for schema assessment and conversion, not for efficient query-based data export to S3.
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 the SELECT INTO OUTFILE S3 extension to export the query results directly to S3.
Amazon RDS for MySQL supports the `SELECT INTO OUTFILE S3` extension, which allows you to export the results of complex queries (including joins) directly to Amazon S3 in a single, efficient operation. This avoids the overhead of intermediate staging or manual file transfers, making it the most efficient method for exporting a subset of data to S3 for Athena analysis.
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 the COPY command from Amazon Redshift to pull data from RDS.
Why it's wrong here
COPY command imports data into Redshift, not export from RDS.
- ✓
Use the SELECT INTO OUTFILE S3 extension to export the query results directly to S3.
Why this is correct
This RDS feature allows exporting arbitrary SQL query results to S3.
- ✗
Use the AWS Schema Conversion Tool (SCT) to extract the data to S3.
Why it's wrong here
SCT is for schema conversion, not data export.
- ✗
Use mysqldump to export the tables and then upload the files to S3.
Why it's wrong here
mysqldump exports table by table, not a query result with joins; requires post-processing.
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 |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
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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.