DBS-C01 Workload-Specific Database Design Practice Question
A gaming company uses Amazon DynamoDB to store player profiles. Each profile is about 5 KB and is accessed frequently. The access pattern is mostly point reads by player ID. The company wants to reduce read costs while maintaining low latency. Currently, the table uses provisioned capacity with 3000 RCU. Which change would be MOST effective?
⚠ Common exam trap
Many candidates think reducing provisioned capacity (Option C) is sufficient, but they overlook that adaptive capacity only handles short-term bursts and does not prevent throttling from sustained high read traffic, whereas DAX directly reduces the read load on the table.
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 DynamoDB Accelerator (DAX) to cache frequently accessed items.
DynamoDB Accelerator (DAX) provides an in-memory cache that can serve frequently accessed items (like player profiles) with microsecond latency, reducing the number of read requests that hit the underlying table. Since each profile is 5 KB and accessed via point reads, DAX can absorb a significant portion of the read traffic, allowing you to lower provisioned RCU without sacrificing performance. This directly reduces read costs while maintaining low latency, making it the most effective solution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use strongly consistent reads instead of eventually consistent reads.
Why it's wrong here
Strongly consistent reads consume more RCU, increasing costs.
- ✗
Switch from provisioned capacity to on-demand capacity mode.
Why it's wrong here
On-demand is more expensive for steady workloads.
- ✗
Decrease the provisioned RCU to 2000 and rely on adaptive capacity.
Why it's wrong here
Adaptive capacity does not reduce RCU consumption; throttling would occur.
- ✓
Use DynamoDB Accelerator (DAX) to cache frequently accessed items.
Why this is correct
DAX reduces reads from the table, lowering RCU consumption.
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