DEA-C01 Data Store Management Practice Question
Which TWO of the following are benefits of using Amazon DynamoDB Accelerator (DAX)? (Choose TWO.)
⚠ Common exam trap
Many candidates confuse DAX's read acceleration with write performance improvements, or assume that a cache provides durability guarantees similar to the underlying database.
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
✓
Provides microsecond read latency
Option B is correct because DAX is an in-memory write-through cache placed in front of DynamoDB that serves eventually consistent reads from RAM, delivering microsecond read latency for cached items instead of the single-digit millisecond latency of direct DynamoDB reads. Option C is correct because read requests that hit the DAX cache are answered by DAX itself, so they never reach the DynamoDB table, which offloads read traffic and reduces the read capacity units consumed on the underlying table. Option A is not correct because DAX does not accelerate writes: write operations are still written through to DynamoDB synchronously, so write throughput and write latency remain governed by the table. Option D is not correct because durability across Availability Zones is provided by DynamoDB's own multi-AZ replication of table data, not by DAX, which is a cache and can lose cached data. Option E is not correct because DAX does not reduce the storage consumed by the DynamoDB table; it is an additional caching layer that itself incurs cost.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Improves write throughput
Why it's wrong here
DAX caches read results in memory, accelerating eventually consistent reads, but writes still pass through to the underlying DynamoDB table, so write throughput is unchanged. It is tempting because DAX is marketed as a performance accelerator, and it would be the right choice when read latency on hot keys is the bottleneck.
- ✓
Provides microsecond read latency
Why this is correct
DAX is an in-memory write-through cache sitting in front of DynamoDB, serving eventually consistent reads from RAM in microseconds rather than the single-digit millisecond latency of direct DynamoDB access. This satisfies the microsecond read latency benefit.
- ✓
Offloads read traffic from the DynamoDB table
Why this is correct
Because DAX answers cache hits itself, those reads never reach the DynamoDB table, reducing consumed read capacity units and relieving pressure on the underlying table. This offloading of read traffic is the benefit, distinct from latency reduction.
- ✗
Provides data durability across Availability Zones
Why it's wrong here
DAX is a write-through in-memory cache in front of DynamoDB; durability remains DynamoDB's responsibility, replicated across Availability Zones by the table itself. It is tempting because DAX does improve read latency and throughput dramatically, and availability-zone resilience is a genuine DynamoDB property, just not one DAX provides.
- ✗
Reduces storage costs
Why it's wrong here
DAX adds a caching tier with its own cluster nodes, so it increases cost rather than reducing storage spend; item storage in DynamoDB is unaffected. It is tempting because caching can lower read request charges and provisioned read capacity, which is a throughput-cost saving, not a storage-cost saving.
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