- A
Partition the table by order_date using PostgreSQL declarative partitioning.
Why wrong: Partitioning can help with data management but may not improve query performance without proper indexing.
- B
Upgrade to a larger RDS instance type.
Why wrong: Hardware upgrade may improve performance but does not optimize the query plan.
- C
Enable RDS Performance Insights to identify bottlenecks.
Why wrong: This is a monitoring tool, not a design change to improve performance.
- D
Create a composite index on (customer_id, order_date).
A composite index supports queries filtering by both columns efficiently.
Question 1,165 of 1,730
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company runs an OLTP application on Amazon RDS for PostgreSQL. The database stores customer orders. The application frequently queries orders by customer_id and order_date. The orders table has 100 million rows. The query performance has degraded over time. The database has a single index on customer_id. The company needs to improve query performance without changing the application code. Which design change should be made?
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
✓
Create a composite index on (customer_id, order_date).
The query performance has degraded because the existing single-column index on customer_id can filter by customer but still requires a full sort or scan within that customer's rows to satisfy the order_date condition. Creating a composite index on (customer_id, order_date) allows the database to use a single index seek to locate the exact rows matching both columns, eliminating the need for an additional sort or filter pass. This directly addresses the query pattern without any application code changes.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Partition the table by order_date using PostgreSQL declarative partitioning.
Why it's wrong here
Partitioning can help with data management but may not improve query performance without proper indexing.
- ✗
Upgrade to a larger RDS instance type.
Why it's wrong here
Hardware upgrade may improve performance but does not optimize the query plan.
- ✗
Enable RDS Performance Insights to identify bottlenecks.
Why it's wrong here
This is a monitoring tool, not a design change to improve performance.
- ✓
Create a composite index on (customer_id, order_date).
Why this is correct
A composite index supports queries filtering by both columns efficiently.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose partitioning (Option A) because they think it automatically speeds up queries, but without changing the query to leverage partition pruning, partitioning alone does not improve index-based lookups; the correct solution is to add a covering composite index that matches the query filter order.
Detailed technical explanation
How to think about this question
PostgreSQL's B-tree index can store multiple columns in a composite index, and the order of columns matters: the leading column (customer_id) enables efficient equality lookups, while the second column (order_date) is stored in sorted order within each customer_id, allowing the database to satisfy range scans or ORDER BY without additional sorting. Under the hood, the index leaf pages contain tuples sorted by the first key, then the second, so a query like WHERE customer_id = ? AND order_date BETWEEN ? AND ? can perform a single index range scan. In a real-world scenario with 100 million rows, this can reduce query time from minutes to milliseconds.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a composite index on (customer_id, order_date). — The query performance has degraded because the existing single-column index on customer_id can filter by customer but still requires a full sort or scan within that customer's rows to satisfy the order_date condition. Creating a composite index on (customer_id, order_date) allows the database to use a single index seek to locate the exact rows matching both columns, eliminating the need for an additional sort or filter pass. This directly addresses the query pattern without any application code changes.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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