CLF-C02 Cloud Technology and Services Practice Question
Which AWS service enables you to run relational database workloads with up to 5x the throughput of standard MySQL and 3x the throughput of standard PostgreSQL at a lower price point than commercial databases?
⚠ Common exam trap
A common mix-up: candidates confuse Amazon RDS for MySQL with Amazon Aurora, assuming RDS offers the same performance enhancements, but Aurora is a separate engine with a fundamentally different distributed architecture that provides the stated throughput gains.
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
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, offering up to 5x the throughput of standard MySQL and 3x the throughput of standard PostgreSQL. It achieves this performance through a distributed, auto-healing storage subsystem that separates compute from storage, and it is priced lower than commercial databases like Oracle or SQL Server while providing high availability and durability.
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 MySQL
Why it's wrong here
Amazon RDS for MySQL correctly runs the MySQL engine and is fully managed, but its architecture relies on a single primary database instance with Amazon EBS storage attached, without Aurora's purpose-built distributed storage layer. This limits its write and read throughput compared to Aurora, which separates storage into a multi-node cluster with six replicas across three Availability Zones and offloads redo processing to storage. Therefore, RDS for MySQL does not achieve the 5x throughput improvement described in the scenario.
- ✓
Amazon Aurora
Why this is correct
Amazon Aurora is the correct choice because its distributed, SSD-backed virtual storage layer is purpose-built to deliver up to 5x the throughput of standard MySQL and 3x that of PostgreSQL, while maintaining compatibility with those engines. Storage is replicated six ways across three Availability Zones, and redo logging is pushed to storage to reduce network and CPU overhead, enabling high write performance. Aurora also supports MySQL and PostgreSQL clients without modification, making it a drop-in relational database with superior performance and built-in high availability.
- ✗
Amazon Redshift
Why it's wrong here
Amazon Redshift is a columnar data warehouse designed for online analytical processing (OLAP) of petabytes of data using massive parallel processing, not for online transaction processing (OLTP) or MySQL compatibility. It is not a relational database for high-frequency insert/update operations and lacks the MySQL wire protocol. Because the scenario calls for a MySQL-compatible database serving a transactional application with high throughput, Redshift's analytical orientation makes it an incorrect option.
- ✗
Amazon DynamoDB
Why it's wrong here
Amazon DynamoDB is a fully managed NoSQL key-value and document database that uses a proprietary API and supports flexible schemas. It cannot run MySQL or PostgreSQL engines because it is non-relational and lacks their SQL capabilities, joins, and transactional semantics. While it offers single-digit millisecond latency at scale, it is not designed for MySQL-compatible relational workloads.
Visual reference
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This CLF-C02 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 CLF-C02 exam.