MLS-C01 Data Engineering Practice Question
A company uses Amazon DynamoDB as the primary data store for a real-time recommendation engine. The data engineering team needs to export a daily snapshot of the DynamoDB table to S3 for offline analytics. The table is large (10 TB) and has a high read/write throughput. Which method will export the data with the least impact on the production workload?
⚠ Common exam trap
A common mix-up: candidates assume any data extraction from DynamoDB must use the Scan API (options A, B, D) and overlook the native export feature that bypasses the live table entirely, which is the only zero-impact method for large, high-throughput tables.
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 DynamoDB export to S3 feature available in the AWS Console or CLI.
The native DynamoDB export to S3 feature uses the table's internal backup mechanism (point-in-time recovery) to export data without consuming any read capacity units (RCUs) from the production table. This ensures zero impact on the live workload, even for a 10 TB table with high throughput.
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 AWS Data Pipeline to export the DynamoDB table to S3.
Why it's wrong here
Data Pipeline also uses scan operations, consuming RCUs.
- ✗
Use DynamoDB Scan API with parallel scans to export data to S3.
Why it's wrong here
Scan operations consume read capacity units and impact production workload.
- ✓
Use the DynamoDB export to S3 feature available in the AWS Console or CLI.
Why this is correct
This feature exports data without consuming read capacity units, minimizing impact.
- ✗
Use AWS Glue ETL job with a DynamoDB connection to export data.
Why it's wrong here
Glue ETL also reads from DynamoDB using scan, consuming RCUs.
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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This MLS-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 MLS-C01 exam.