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A global e-commerce company experiences highly variable traffic patterns, with significant spikes during promotional events and seasonal sales. The company's primary database is a relational database hosted on Amazon EC2, which struggles to scale efficiently during peak loads. They need a database solution that can automatically scale capacity up and down to meet demand without manual intervention, while maintaining high performance and availability. Which AWS database service is most suitable for this requirement?
- AAmazon DynamoDB
- BAmazon Redshift
- CAmazon Aurora Serverless v2
- DAmazon RDS for PostgreSQL with Provisioned IOPS
Show answer & explanationAnswer & explanation
Correct answer: C. Amazon Aurora Serverless v2
Amazon Aurora Serverless v2 automatically scales compute and memory capacity based on demand, providing high performance and availability for variable workloads. It eliminates the need for manual provisioning and management of database instances.
Why the other options are wrong
- A. Amazon DynamoDB is a NoSQL database, and while highly scalable, the scenario specifies a relational database requirement.
- B. Amazon Redshift is a data warehousing service, optimized for analytical workloads, not transactional relational databases for an e-commerce application.
- D. Amazon RDS with Provisioned IOPS requires manual scaling of instance types and storage, which is not ideal for highly variable, unpredictable workloads.
Amazon Aurora Serverless v2
A serverless deployment option for Amazon Aurora that automatically scales database capacity up and down based on application demand, without manual intervention.
- Scales compute and memory capacity in fine-grained increments.
- Pay-per-use for capacity consumed.
- Ideal for unpredictable, spiky workloads.
- Compatible with MySQL and PostgreSQL.
Memory trick: Aurora scales like a chameleon, blending with demand.