The answer is DynamoDB Accelerator (DAX) for in-memory caching. This is correct because high-traffic gaming leaderboards face uneven access patterns where a small set of top scores are read millions of times per second, creating hot partitions that can throttle the main table. DAX offloads this read-heavy traffic by caching the most frequently queried data in memory, reducing latency from single-digit milliseconds to microseconds and preventing throttling under load. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of DynamoDB performance optimization for real-time leaderboards—a common scenario where candidates mistakenly choose Global Secondary Indexes or write sharding instead of caching. The trap is that while GSIs help with query flexibility, they don’t solve read-hotspot throttling; DAX does. Remember the mnemonic: “DAX Deflects Hot Reads” to recall that caching, not indexing, handles bursty leaderboard traffic.
DEA-C01 Data Store Management Practice Question
This DEA-C01 practice question tests your understanding of data store management. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE considerations are important when designing a DynamoDB table for high-traffic gaming leaderboards? (Choose three.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable DynamoDB Accelerator (DAX) for low-latency reads
DynamoDB Accelerator (DAX) provides in-memory caching for DynamoDB tables, reducing read latency from single-digit milliseconds to microseconds. For high-traffic gaming leaderboards, where millions of players query scores concurrently, DAX offloads read traffic from the main table, preventing throttling and ensuring consistent low-latency responses for the most frequently accessed data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 for all queries
Why it's wrong here
Strongly consistent reads are slower and reduce throughput.
✓
Enable DynamoDB Accelerator (DAX) for low-latency reads
Why this is correct
DAX provides caching for fast reads.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use Time to Live (TTL) to automatically expire old scores
Why this is correct
TTL removes old data to maintain performance.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use DynamoDB Adaptive Capacity to handle uneven access patterns
Why this is correct
Adaptive capacity helps with hot partitions.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable DynamoDB Streams for real-time updates
Why it's wrong here
Streams are for change data capture, not directly for leaderboards.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse DynamoDB Streams with a read-acceleration feature, but Streams are strictly for change data capture and do not reduce query latency or handle high read throughput.
Detailed technical explanation
How to think about this question
DAX maintains a write-through cache that is transparent to the application; when a write occurs, DAX updates the cache and the underlying DynamoDB table synchronously. For leaderboards, DAX can be configured with a TTL for cached items to ensure stale scores are evicted, and it supports both eventually consistent and strongly consistent reads from the cache, though the latter incurs a small overhead. In a real-world scenario, a game with 1 million concurrent players querying the top 100 scores every second would overwhelm the table's provisioned RCUs, but DAX can absorb 99% of those reads with sub-millisecond latency.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable DynamoDB Accelerator (DAX) for low-latency reads — DynamoDB Accelerator (DAX) provides in-memory caching for DynamoDB tables, reducing read latency from single-digit milliseconds to microseconds. For high-traffic gaming leaderboards, where millions of players query scores concurrently, DAX offloads read traffic from the main table, preventing throttling and ensuring consistent low-latency responses for the most frequently accessed data.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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