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Workload-Specific Database DesignmediumMultiple SelectObjective-mapped

DBS-C01 Workload-Specific Database Design Practice Question

Which TWO of the following are best practices for designing a DynamoDB table for high traffic? (Choose 2)

⚠ Common exam trap

AWS often tests the misconception that strongly consistent reads always provide better performance, when in fact they are more expensive and slower than eventually consistent reads, and should only be used when strict read-after-write consistency is required.

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

Use global secondary indexes for alternate access patterns

Global secondary indexes (GSIs) allow you to define alternate partition and sort keys to support different query patterns without duplicating data. This is a best practice for high-traffic workloads because it enables efficient access to data using multiple access patterns while maintaining a single base table, reducing the need for expensive scans or application-level joins.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Store large items to reduce the number of items

    Why it's wrong here

    Large items can exceed DynamoDB's item size limit and cause throttling.

  • Use normalized tables and perform joins in application

    Why it's wrong here

    DynamoDB is NoSQL and does not support joins; design for single-table access.

  • Use global secondary indexes for alternate access patterns

    Why this is correct

    GSIs allow efficient queries on non-key attributes.

  • Always use strongly consistent reads for best performance

    Why it's wrong here

    Strongly consistent reads consume more throughput and are not always necessary.

  • Use partition keys with high cardinality

    Why this is correct

    High cardinality ensures even distribution of requests across partitions.

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