DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. 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.
A company uses Amazon DynamoDB to store IoT sensor data. Each sensor sends data every minute. The table has a partition key of sensor_id and a sort key of timestamp. The application queries data for a sensor over the last hour. The table uses on-demand capacity. Recently, the query latency increased for sensors that generate a high volume of data. The application retrieves all attributes for the sensor data. Which design change should be made to reduce latency?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a global secondary index (GSI) with the same key structure but projecting only the required attributes.
Option B is correct because creating a GSI with the same key structure but projecting only the required attributes reduces the amount of data read from the base table. Since the application retrieves all attributes, but the GSI can be designed to project only the necessary columns, this minimizes read I/O and reduces latency. This is especially effective for sensors with high data volume, as it avoids fetching large item payloads from the base table.
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 DynamoDB Accelerator (DAX) for the table.
Why it's wrong here
DAX caches frequently accessed data but does not reduce the read size for all queries.
✓
Create a global secondary index (GSI) with the same key structure but projecting only the required attributes.
Why this is correct
A GSI with projected attributes reduces the amount of data read, lowering latency.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable DynamoDB Streams to replicate data to Amazon ElastiCache.
Why it's wrong here
This adds complexity and may increase latency due to additional hops.
✗
Increase the read capacity units (RCUs) on the table.
Why it's wrong here
On-demand already scales; increasing RCUs is not applicable.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume DAX is the universal solution for read latency, but the real issue is the volume of data read per query, not cache misses, making GSI projection the correct optimization.
Detailed technical explanation
How to think about this question
When a DynamoDB query retrieves all attributes, it reads the entire item from the base table, including any large or unused attributes. A GSI with projected attributes allows the query to read only the needed columns from the index, which is typically smaller and faster. Under the hood, DynamoDB charges for read capacity based on the size of the items read, so projecting fewer attributes reduces both latency and cost. In real-world scenarios, IoT sensors often store metadata or raw payloads that are not needed for time-series queries, making GSI projection a key optimization.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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.
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a global secondary index (GSI) with the same key structure but projecting only the required attributes. — Option B is correct because creating a GSI with the same key structure but projecting only the required attributes reduces the amount of data read from the base table. Since the application retrieves all attributes, but the GSI can be designed to project only the necessary columns, this minimizes read I/O and reduces latency. This is especially effective for sensors with high data volume, as it avoids fetching large item payloads from the base table.
What should I do if I get this DBS-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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