DBS-C01 Workload-Specific Database Design Practice Question

Which THREE design patterns are commonly used to optimize DynamoDB performance for write-heavy workloads?

⚠ Common exam trap

Many candidates confuse global tables (Option E) as a write optimization technique, but it is primarily a replication feature for availability and read performance, not a direct write throughput optimization.

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

✓

Using DynamoDB adaptive capacity to handle unbalanced access patterns.

DynamoDB adaptive capacity automatically isolates heavily accessed partitions, allowing them to consume more throughput without throttling other partitions. This is critical for write-heavy workloads with uneven access patterns, as it prevents hot partitions from degrading overall performance.

Answer analysis

Option-by-option breakdown

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

✓
Using DynamoDB adaptive capacity to handle unbalanced access patterns.
Why this is correct
Adaptive capacity automatically rebalances partitions to handle hot spots.
✗
Using sparse indexes on rarely accessed attributes.
Why it's wrong here
Sparse indexes are for read efficiency, not writes.
✓
Batch writes using BatchWriteItem.
Why this is correct
Batching reduces the number of write requests and improves throughput.
✓
Write sharding using a random suffix on the partition key.
Why this is correct
Distributes writes across partitions to avoid hot spots.
✗
Using global tables to distribute writes across regions.
Why it's wrong here
Global tables replicate data, but do not inherently improve write performance.

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DBS-C01 Workload-Specific Database Design Practice Question

Why each option matters

Option-by-option breakdown

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