The correct answer is to review and remove unnecessary indexes on the collection. This is because in Amazon DocumentDB, every write operation—whether an insert, update, or delete—must update every index defined on the collection, so each extra index adds a direct write penalty that increases latency. For applications performing frequent updates to a small subset of fields, the overhead of maintaining unused indexes becomes a primary bottleneck, making index reduction the most effective way to reduce write latency. On the AWS Certified Database Specialty DBS-C01 exam, this question tests your understanding of DocumentDB’s write path and the trade-off between read performance and write overhead; a common trap is to suggest scaling up instances or enabling sharding, but the immediate, cost-free fix is index hygiene. Remember the mnemonic: “Fewer indexes, faster writes”—if you want to cut write latency, cut the indexes first.
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 is running a MongoDB-compatible database on Amazon DocumentDB. The application performs frequent updates to a small subset of fields in documents. The company notices that write latency is high. What should the database specialist recommend to reduce write latency?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Review and remove unnecessary indexes on the collection.
Option A is correct because unnecessary indexes impose a write penalty on every insert, update, and delete operation. In Amazon DocumentDB, each write must update all indexes on the collection, so removing unused indexes reduces the per-document write overhead and directly lowers write latency for frequent updates to a small subset of fields.
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.
✓
Review and remove unnecessary indexes on the collection.
Why this is correct
Fewer indexes mean less work during writes, reducing latency.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the instance size of the DocumentDB cluster.
Why it's wrong here
While this may improve performance, it does not address root cause if indexes are the issue.
✗
Enable multi-master writes to distribute write load.
Why it's wrong here
DocumentDB supports only single-master writes.
✗
Change the storage type from standard to provisioned IOPS.
Why it's wrong here
DocumentDB uses the same underlying storage; provisioned IOPS is not applicable.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume scaling up hardware (Option B) or changing storage (Option D) is the default fix for high write latency, but the exam tests understanding that index overhead is the most common cause of write amplification in DocumentDB and MongoDB-compatible databases.
Detailed technical explanation
How to think about this question
Under the hood, DocumentDB uses a distributed storage system that replicates data across three Availability Zones. Each index update requires a separate write I/O to the storage layer, so the number of indexes directly multiplies the write cost. For collections with high-frequency updates on a few fields, dropping unused indexes can reduce write latency by 50% or more, as each index adds a B-tree update that must complete before the write is acknowledged.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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: Review and remove unnecessary indexes on the collection. — Option A is correct because unnecessary indexes impose a write penalty on every insert, update, and delete operation. In Amazon DocumentDB, each write must update all indexes on the collection, so removing unused indexes reduces the per-document write overhead and directly lowers write latency for frequent updates to a small subset of fields.
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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