DBS-C01 Workload-Specific Database Design Practice Question
A company is migrating an on-premises Oracle data warehouse to AWS. The warehouse contains 50 TB of data and runs complex queries that involve joins and aggregations. The team wants to minimize migration effort and cost while maintaining query performance. Which AWS service should they use?
⚠ Common exam trap
It's easy for candidates to choose Amazon RDS for Oracle because it seems like a direct lift-and-shift, but they overlook that RDS is not designed for analytical workloads at this scale, whereas Redshift is the only AWS service built specifically for petabyte-scale data warehousing with MPP and columnar storage.
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 Redshift
Amazon Redshift is purpose-built for large-scale data warehousing, supporting up to petabytes of data with massively parallel processing (MPP) architecture that efficiently handles complex joins and aggregations. It minimizes migration effort by supporting automated schema conversion from Oracle via the AWS Schema Conversion Tool (SCT) and cost-effective columnar storage with compression, making it the optimal choice for a 50 TB Oracle data warehouse migration.
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 RDS for Oracle
Why it's wrong here
RDS is for OLTP and cannot handle data warehouse workloads efficiently.
- ✗
Amazon ElastiCache for Redis
Why it's wrong here
ElastiCache is a cache, not a data warehouse.
- ✓
Amazon Redshift
Why this is correct
Redshift is purpose-built for large-scale data warehousing and analytics.
- ✗
Amazon DynamoDB
Why it's wrong here
DynamoDB is key-value and not designed for complex joins.
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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