- A
Amazon Aurora Serverless v2
Automatically scales capacity and is cost-effective for variable workloads.
- B
Amazon DynamoDB with on-demand capacity
Why wrong: DynamoDB is NoSQL, not suitable for complex analytical queries.
- C
Amazon RDS for MySQL with a Single-AZ deployment
Why wrong: Does not automatically scale; requires manual scaling.
- D
Amazon Redshift Serverless
Why wrong: Redshift is optimized for analytics, not transactional workloads.
Question 439 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 startup needs a cost-effective database for a small application that handles both transactional and analytical workloads. They expect low traffic initially but want the database to automatically scale as the business grows. Which database solution is BEST suited?
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 Aurora Serverless v2
Amazon Aurora Serverless v2 is the best fit because it automatically scales compute and memory capacity in fine-grained increments (down to 1 ACU) based on actual workload demand, supporting both transactional (OLTP) and analytical (OLAP) queries via the MySQL/PostgreSQL-compatible Aurora engine. It offers a pay-per-ACU model that is cost-effective for low-traffic startups while providing near-instant scaling to handle growth without manual intervention.
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.
- ✓
Amazon Aurora Serverless v2
Why this is correct
Automatically scales capacity and is cost-effective for variable workloads.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon DynamoDB with on-demand capacity
Why it's wrong here
DynamoDB is NoSQL, not suitable for complex analytical queries.
- ✗
Amazon RDS for MySQL with a Single-AZ deployment
Why it's wrong here
Does not automatically scale; requires manual scaling.
- ✗
Amazon Redshift Serverless
Why it's wrong here
Redshift is optimized for analytics, not transactional workloads.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'serverless' with 'NoSQL' (DynamoDB) or assume that any 'serverless' database (Redshift Serverless) can handle mixed workloads, but the key differentiator is the need for relational SQL support for both transactional and analytical queries, which only Aurora Serverless v2 provides among the options.
Detailed technical explanation
How to think about this question
Aurora Serverless v2 uses a shared storage volume that decouples compute from storage, allowing ACU (Aurora Capacity Unit) scaling in 0.5 ACU increments with sub-second latency, while maintaining full MySQL/PostgreSQL compatibility for both transactional and analytical queries. Under the hood, it leverages a distributed, multi-tenant fleet of warm pools to rapidly allocate capacity, and it supports reader endpoints for read-heavy analytical workloads without impacting write performance. In a real-world scenario, a startup with a customer-facing app that runs monthly reports can use Aurora Serverless v2 to avoid over-provisioning during low-traffic periods and automatically scale during peak reporting cycles.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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: Amazon Aurora Serverless v2 — Amazon Aurora Serverless v2 is the best fit because it automatically scales compute and memory capacity in fine-grained increments (down to 1 ACU) based on actual workload demand, supporting both transactional (OLTP) and analytical (OLAP) queries via the MySQL/PostgreSQL-compatible Aurora engine. It offers a pay-per-ACU model that is cost-effective for low-traffic startups while providing near-instant scaling to handle growth without manual intervention.
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.
About these practice questions
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Last reviewed: Jun 24, 2026
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