- A
Use a simple primary key (sensor ID) and scan the table filtering by timestamp
Why wrong: Scan is expensive and slow for large tables.
- B
Use a composite primary key: partition key = sensor ID, sort key = timestamp
This allows efficient range queries on timestamp for a sensor.
- C
Use a composite primary key: partition key = timestamp, sort key = sensor ID
Why wrong: This would scatter data across partitions but still require a scan for a sensor.
- D
Use a simple primary key (sensor ID) and a global secondary index on timestamp
Why wrong: GSI adds cost and querying by sensor ID then filtering by timestamp is less efficient.
Question 1,719 of 1,730
Designing a DynamoDB Table for Time Series Data with Composite Primary Key
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 writes a record every second, and the application needs to query the last 24 hours of data for a specific sensor. The query must be very fast. Which table design and query pattern will minimize cost and latency?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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 a composite primary key: partition key = sensor ID, sort key = timestamp
Option B is correct because using a composite primary key with partition key = sensor ID and sort key = timestamp allows DynamoDB to efficiently query all items for a specific sensor in a single partition, using the Query API with a sort key condition on timestamp. This design ensures fast, targeted reads without scanning, minimizing read capacity units and latency.
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 a simple primary key (sensor ID) and scan the table filtering by timestamp
Why it's wrong here
Scan is expensive and slow for large tables.
- ✓
Use a composite primary key: partition key = sensor ID, sort key = timestamp
Why this is correct
This allows efficient range queries on timestamp for a sensor.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a composite primary key: partition key = timestamp, sort key = sensor ID
Why it's wrong here
This would scatter data across partitions but still require a scan for a sensor.
- ✗
Use a simple primary key (sensor ID) and a global secondary index on timestamp
Why it's wrong here
GSI adds cost and querying by sensor ID then filtering by timestamp is less efficient.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Option C, mistakenly thinking that timestamp as a partition key provides global time ordering, but this actually scatters sensor data across partitions, making per-sensor queries impossible without a full scan.
Detailed technical explanation
How to think about this question
Under the hood, DynamoDB's Query operation on a composite primary key uses the partition key to locate the exact partition and then leverages the sort key's ordered index to retrieve only the items within the requested timestamp range, achieving O(log n) efficiency. In a real-world IoT scenario with millions of sensors, this design avoids hot partitions by ensuring each sensor's data stays within its own partition, while the sort key enables time-based range queries without additional indexing overhead.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
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: Use a composite primary key: partition key = sensor ID, sort key = timestamp — Option B is correct because using a composite primary key with partition key = sensor ID and sort key = timestamp allows DynamoDB to efficiently query all items for a specific sensor in a single partition, using the Query API with a sort key condition on timestamp. This design ensures fast, targeted reads without scanning, minimizing read capacity units and latency.
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.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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