Cost-Effective Scalable Database for Structured Data

SAA-C03 By islever Editorial Last updated

Design cost-optimized database solutions.

Short answer

C Use Amazon Aurora Serverless for the database. Use serverless capacity scaling. Configure automated backups to Amazon S3.

Question

A company is launching a new application that requires a structured database to store user profiles, application settings, and transactional data. The database must be scalable with application traffic and must offer backups. Which solution will meet these requirements MOST cost-effectively?
  1. Deploy a self-managed database on Amazon EC2 instances by using open source software. Use Spot Instances for cost optimization. Configure automated backups to Amazon S3.
  2. Use Amazon RDS. Use on-demand capacity mode for the database with General Purpose SSD storage. Configure automatic backups with a retention period of 7 days.
  3. Use Amazon Aurora Serverless for the database. Use serverless capacity scaling. Configure automated backups to Amazon S3. Correct Answer
  4. Deploy a self-managed NoSQL database on Amazon EC2 instances. Use Reserved Instances for cost optimization. Configure automated backups directly to Amazon S3 Glacier Flexible Retrieval.

Key Takeaways

Tests the ability to select a fully managed, auto-scaling database service that eliminates operational overhead while optimizing costs for variable traffic patterns.

Determines the most cost-effective scalable database solution for structured data using Amazon Aurora Serverless. This page explains why managed serverless architecture outperforms self-managed or provisioned options for spiky workloads.

Common mistake: Learners often choose Option B (Amazon RDS On-Demand) assuming standard managed services are always cheaper, failing to recognize that Aurora Serverless provides better cost efficiency for unpredictable, spiky traffic by scaling to zero.

Expert Analysis

Why the Answer Is Correct

Option C is the correct choice because Amazon Aurora Serverless is a fully managed relational database engine that automatically provisions and scales compute capacity based on actual usage. For an application with variable traffic ('scalable with application traffic'), this 'scale-to-zero' capability ensures you only pay for what you use, making it the most cost-effective solution among the options. It handles backups natively and requires no infrastructure management.

Why the Other Options Are Wrong

Option A is incorrect because running a database on EC2 Spot Instances is risky; Spot Instances can be terminated with little notice, which is unacceptable for persistent structured data like user profiles. Option B uses On-Demand capacity, which charges for full instance availability regardless of load, making it less cost-effective than Serverless for spiky workloads. Option D involves managing a NoSQL database on EC2, which introduces significant operational overhead and lacks the automatic scalability and ease of backup integration provided by managed services.

Community Comment Notes

The community consensus strongly supports Option C, noting that Spot Instances are unsuitable for databases due to termination risks. As LeonSauveterre noted, "Spot Instance is never a good idea for databases" because they cannot handle the persistence requirements. Aragon_saa simply confirmed the answer is C, reflecting the clear advantage of serverless architectures in this scenario.

Exam Strategy

When asked for the 'most cost-effective' solution for variable workloads, prioritize managed serverless options (like Aurora Serverless or DynamoDB On-Demand) over provisioned instances (RDS On-Demand) because they scale down to zero when idle. Always eliminate self-managed options (EC2) if the question emphasizes cost-effectiveness and ease of maintenance.

Frequently Asked Questions

Why is Amazon RDS On-Demand not the best cost option?

On-Demand RDS charges for the entire instance capacity continuously, even during low traffic. Aurora Serverless scales down to zero compute units, reducing costs significantly for spiky workloads.

Can I use Spot Instances for production databases?

Generally no. Spot Instances can be interrupted with a two-minute warning, leading to potential data loss or downtime. Databases require high availability and persistence that Spot Instances cannot guarantee.

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Community Votes

C
100%

100% of anonymous learners picked answer C. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 2 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 2

  1. LeonSauveterre 👍 2 Answered C
    A - Spot Instance is never a good idea for databases. These instances can be terminated with little notice, while databases are almost always persistent workloads. B - On-Demand Capacity is suitable for steady or predictable workloads, but not as cost-efficient as Aurora Serverless for spiky or unpredictable workloads. C - Aurora Serverless is a fully managed relational database that scales automatically with traffic. Automated Backups is also integrated with Aurora. Good! D - We need a structured database, not NoSQL database.
  2. aragon_saa 👍 5 Answered C
    Answer is C

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