Amazon Aurora is the correct choice because it uniquely supports both OLTP and read-heavy analytics workloads while providing high availability and automatic failover with minimal downtime. Aurora achieves this through six-way replication across three Availability Zones, enabling automatic failover in under 30 seconds, and supports up to 15 low-latency read replicas that can offload analytics queries without impacting write performance. On the AWS Certified Database Specialty DBS-C01 exam, this scenario tests your understanding of how Aurora bridges transactional and analytical demands, often appearing as a trap where candidates might incorrectly choose a separate analytics service like Redshift or a NoSQL option like DynamoDB. The key distinction is that Aurora handles mixed workloads natively, whereas Redshift is optimized for pure analytics at scale. For the exam, remember the memory tip: “Aurora for both, Redshift for the big batch” — Aurora excels when you need real-time analytics alongside OLTP without sacrificing write throughput or failover speed.
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 is designing a database for an e-commerce platform that requires high availability and automatic failover with minimal downtime. The application performs both OLTP and read-heavy analytics. Which AWS database service should be used?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Amazon Aurora
Amazon Aurora is the correct choice because it combines the high availability and automatic failover of a relational database with the performance needed for both OLTP and read-heavy analytics. Aurora provides six-way replication across three Availability Zones, automatic failover in under 30 seconds, and supports up to 15 low-latency read replicas that can offload analytics queries without impacting write performance.
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 DynamoDB
Why it's wrong here
DynamoDB is a NoSQL database and does not support complex relational queries typical in OLTP.
✗
Amazon RDS for MySQL
Why it's wrong here
RDS for MySQL has limited read replica support and slower failover compared to Aurora.
✗
Amazon Redshift
Why it's wrong here
Redshift is optimized for analytics and data warehousing, not for OLTP workloads.
✓
Amazon Aurora
Why this is correct
Aurora offers high availability, automatic failover, and up to 15 read replicas for analytics.
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 Amazon RDS for MySQL because they assume Multi-AZ provides automatic failover and read replicas for analytics, but they overlook that Aurora offers faster failover, better read replica performance, and integrated storage replication without the need for separate Multi-AZ configuration.
Detailed technical explanation
How to think about this question
Under the hood, Aurora uses a distributed, shared-storage volume that separates compute from storage, allowing the database to automatically repair corrupted data pages and recover from crashes in seconds without replaying the redo log. The read replicas in Aurora share the same underlying storage volume, so they can serve read traffic with minimal replication lag (typically under 100ms) and can be promoted to primary in under a minute during a failover. In a real-world e-commerce scenario, this means the platform can handle peak holiday traffic with thousands of concurrent transactions while simultaneously running inventory and sales analytics queries on replicas without degrading write performance.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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.
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 — Amazon Aurora is the correct choice because it combines the high availability and automatic failover of a relational database with the performance needed for both OLTP and read-heavy analytics. Aurora provides six-way replication across three Availability Zones, automatic failover in under 30 seconds, and supports up to 15 low-latency read replicas that can offload analytics queries without impacting write performance.
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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Question Discussion
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