AWS Certified Data Engineer Associate · Free Practice Question Medium
Question 55
A data engineering team is developing a new application that requires intermittent access to a relational database. The application’s usage is expected to have unpredictable peaks and valleys. The team stores the application data in Amazon S3 and needs an on-demand relational database solution that can automatically scale to match the application’s workload and minimize operational management and cost.
Which AWS service should the data engineering team use to meet the application’s database requirements with auto-scaling capabilities and direct integration with Amazon S3?
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A
Use Amazon Aurora Serverless with an S3 integration, enabling the database to scale automatically with the application's demand.
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B
Set up an Amazon DynamoDB table with auto-scaling enabled and stream data from S3 using AWS Lambda functions for relational database-like operations.
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C
Implement Amazon Redshift with automatic pause and resume based on the activity levels to optimize cost and performance.
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D
Configure Amazon RDS with a scaling policy to adjust the compute resources based on the application's workload.
Reveal correct answer
Correct answer: A
Explanation
Amazon Aurora Serverless is a fully managed database service that automatically starts up, shuts down, and scales capacity up or down based on your application's needs. It’s designed for applications with unpredictable workloads, and it integrates with Amazon S3, allowing easy data import/export for further processing.
This service suits the data engineering team’s need for a relational database with minimal operational overhead, cost-efficiency, and the capability to handle the variable workload without manual scaling.
CORRECT: "Use Amazon Aurora Serverless with an S3 integration, enabling the database to scale automatically with the application's demand" is the correct answer (as explained above.)
INCORRECT: "Configure Amazon RDS with a scaling policy to adjust the compute resources based on the application's workload" is incorrect.
Amazon RDS does allow for scaling, but it does not automatically adjust compute resources in real-time in response to active connections, which means it could either under-provision or over-provision resources compared to the serverless model.
INCORRECT: "Implement Amazon Redshift with automatic pause and resume based on the activity levels to optimize cost and performance" is incorrect.
Amazon Redshift is a powerful data warehousing service that can now automatically pause and resume; however, it’s optimized for complex analytical queries over large datasets rather than serving as an on-demand operational database.
INCORRECT: "Set up an Amazon DynamoDB table with auto-scaling enabled and stream data from S3 using AWS Lambda functions for relational database-like operations" is incorrect.
Amazon DynamoDB offers auto scaling and high performance for applications, but it is a NoSQL service and does not provide relational database features natively. Complex workarounds would be needed to mimic relational operations, which adds unnecessary complexity for a data engineering task.
References:
https://aws.amazon.com/rds/aurora/serverless/
Save time with our AWS cheat sheets:
https://digitalcloud.training/aws-certified-data-engineer-associate-cheat-sheet/
Discussion
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