- A
Amazon DynamoDB with adjacency list design
Why wrong: DynamoDB can model graphs but requires multiple round trips for deep traversals.
- B
Amazon Neptune
Neptune is optimized for graph traversals and supports Gremlin and SPARQL.
- C
Amazon DocumentDB (with MongoDB compatibility)
Why wrong: DocumentDB is document-oriented, not optimized for graph traversals.
- D
Amazon RDS for PostgreSQL with recursive CTEs
Why wrong: Recursive CTEs can handle some graph queries but performance degrades with depth.
Question 381 of 1,730
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. 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 needs to store and query a graph of relationships between users for a recommendation engine. The queries involve traversing multiple edges. Which AWS database service is most suitable?
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
✓
Amazon Neptune
Amazon Neptune is a fully managed graph database service purpose-built for storing and traversing highly connected data. It supports both property graph (Gremlin, openCypher) and RDF (SPARQL) models, making it ideal for recommendation engines that require multi-edge traversals across user relationships.
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.
- ✗
Amazon DynamoDB with adjacency list design
Why it's wrong here
DynamoDB can model graphs but requires multiple round trips for deep traversals.
- ✓
Amazon Neptune
Why this is correct
Neptune is optimized for graph traversals and supports Gremlin and SPARQL.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon DocumentDB (with MongoDB compatibility)
Why it's wrong here
DocumentDB is document-oriented, not optimized for graph traversals.
- ✗
Amazon RDS for PostgreSQL with recursive CTEs
Why it's wrong here
Recursive CTEs can handle some graph queries but performance degrades with depth.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose DynamoDB with adjacency lists (Option A) because they assume any NoSQL database can handle graphs, but they overlook the fundamental architectural mismatch: DynamoDB's partition-based access pattern cannot efficiently support multi-hop traversals without costly fan-out queries.
Detailed technical explanation
How to think about this question
Neptune stores graph data natively as vertices and edges with adjacency pointers, enabling constant-time traversal of relationships without expensive join operations. It uses a shared-storage architecture with automatic replication across three Availability Zones, and supports ACID transactions for graph mutations. For recommendation engines, Neptune can execute Gremlin queries like `g.V().hasLabel('user').repeat(out('follows')).times(3).groupCount().by('interest')` to traverse multiple edges in a single request.
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.
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Workload-Specific Database Design — study guide chapter
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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: Amazon Neptune — Amazon Neptune is a fully managed graph database service purpose-built for storing and traversing highly connected data. It supports both property graph (Gremlin, openCypher) and RDF (SPARQL) models, making it ideal for recommendation engines that require multi-edge traversals across user relationships.
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: Jul 4, 2026
This DBS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DBS-C01 exam.
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