- A
mongoexport and mongoimport
Why wrong: These are for data transfer, not validation.
- B
dbHash command on both databases
Why wrong: dbHash checks consistency of a single instance, not cross-database.
- C
DocumentDB native consistency check tool
Why wrong: DocumentDB does not have a native consistency check tool for migration.
- D
AWS DMS data validation
DMS can validate data between source and target.
Question 1,410 of 1,730
DBS-C01 Deployment and Migration Practice Question
This DBS-C01 practice question tests your understanding of deployment and migration. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 migrating an on-premises MongoDB database to Amazon DocumentDB (with MongoDB compatibility). They want to validate that the data is consistent after migration. Which tool should they use?
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
✓
AWS DMS data validation
AWS DMS data validation is the correct tool because it provides built-in, row-level checksum-based validation that compares source and target data after a full load or ongoing replication. For DocumentDB migrations, DMS can compute and compare checksums on the fly, ensuring consistency without requiring manual scripting or external tools. This is the recommended AWS approach for validating data integrity during and after a migration to DocumentDB.
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.
- ✗
mongoexport and mongoimport
Why it's wrong here
These are for data transfer, not validation.
- ✗
dbHash command on both databases
Why it's wrong here
dbHash checks consistency of a single instance, not cross-database.
- ✗
DocumentDB native consistency check tool
Why it's wrong here
DocumentDB does not have a native consistency check tool for migration.
- ✓
AWS DMS data validation
Why this is correct
DMS can validate data between source and target.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume a native MongoDB command like dbHash or a generic export/import tool can validate consistency across different database engines, but DocumentDB does not support dbHash and AWS DMS is the only service-integrated validation method for cross-engine migrations.
Detailed technical explanation
How to think about this question
AWS DMS data validation works by computing a checksum for each row (or document) using a hash function (e.g., MD5) on the source and target, then comparing results. For DocumentDB, DMS uses the MongoDB wire protocol to read documents and compute checksums, handling BSON types and document ordering carefully. In real-world scenarios, validation can catch silent data corruption or transformation errors that occur during migration, especially when schema conversion or data type mapping is involved.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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?
Deployment and Migration — This question tests Deployment and Migration — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AWS DMS data validation — AWS DMS data validation is the correct tool because it provides built-in, row-level checksum-based validation that compares source and target data after a full load or ongoing replication. For DocumentDB migrations, DMS can compute and compare checksums on the fly, ensuring consistency without requiring manual scripting or external tools. This is the recommended AWS approach for validating data integrity during and after a migration to DocumentDB.
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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Last reviewed: Jun 11, 2026
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