Question 665 of 1,663
DBS-C01 Workload-Specific Database Design Practice Question
A financial services company uses Amazon RDS for MySQL to store transaction data. The database has a single table 'transactions' with 500 million rows. The table has an auto-increment primary key and an index on 'transaction_date'. The company runs a monthly report that aggregates transactions by account_id and transaction_date. The report query uses a GROUP BY on account_id and transaction_date, and scans the entire table. The query takes over 2 hours to complete and often times out. The DBA suggests creating a materialized view. However, the company wants to minimize operational overhead. Which solution meets the requirements with the LEAST operational overhead?
⚠ Common exam trap
Watch out — candidates often assume a larger instance or a composite index can fix any performance issue, but the DBS-C01 exam tests the understanding that analytical workloads require a different engine (Redshift) and that operational overhead includes ongoing maintenance, not just initial setup.
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
✓
Migrate the reporting workload to Amazon Redshift by loading the transactions table into Redshift and running the report query there.
Amazon Redshift is purpose-built for large-scale analytical queries. By migrating the reporting workload to Redshift, the company offloads the heavy aggregation from the transactional RDS instance to a columnar storage engine that can scan and aggregate 500 million rows efficiently using massively parallel processing (MPP). This approach requires no changes to the existing RDS database and minimizes operational overhead compared to managing a materialized view or manual indexing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the RDS instance size to the largest available to improve performance.
Why it's wrong here
Scaling up may help but is not the most efficient; the query still scans 500M rows.
- ✓
Migrate the reporting workload to Amazon Redshift by loading the transactions table into Redshift and running the report query there.
Why this is correct
Redshift is optimized for analytical queries and can handle large aggregations efficiently with minimal operational overhead.
- ✗
Create a materialized view in MySQL that pre-aggregates the data and refreshes it nightly.
Why it's wrong here
MySQL does not natively support materialized views; this requires manual implementation and adds operational overhead.
- ✗
Add a composite index on (account_id, transaction_date) to speed up the GROUP BY.
Why it's wrong here
A composite index does not help a full table scan with aggregation; MySQL may still scan the entire table.
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Last reviewed: Jun 11, 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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