Quick Answer
The answer is Amazon Neptune. This is the correct choice because Neptune is a fully managed graph database service specifically built to handle highly connected data, using graph models like property graph or RDF to efficiently traverse relationships. For a social media application requiring queries such as “mutual friends,” Neptune leverages Gremlin or SPARQL to follow edges between user nodes, making it far more performant than relational or NoSQL alternatives for these recursive, join-heavy patterns. On the AWS Certified Database Specialty DBS-C01 exam, this question tests your ability to match workload patterns to the right database service—graph queries for social networks are a classic Neptune scenario. A common trap is choosing DynamoDB for its scalability, but DynamoDB lacks native graph traversal capabilities, forcing inefficient application-level joins. Remember the mnemonic: “Neptune navigates networks,” so when you see “mutual friends,” “follows,” or “recommendations,” think graph database first.
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 designing a social media application that requires storing user relationships (follows) and making graph queries like 'mutual friends.' Which database is most suitable?
Amazon ElastiCache for Redis
Why wrong: ElastiCache can store graphs but lacks native graph query capabilities.
Amazon DynamoDB
Why wrong: DynamoDB is not efficient for graph traversals.
Amazon Neptune
Neptune is a graph database optimized for highly connected data and graph queries.
Amazon RDS for MySQL
Why wrong: RDS requires complex join queries for graph data, which are inefficient.
Answer choices
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 optimized for storing and querying highly connected data. It supports both property graph and RDF models, and it uses Gremlin or SPARQL to efficiently traverse relationships like 'mutual friends' in a social media application, making it the ideal choice for graph queries.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon ElastiCache for Redis
Why it's wrong here
ElastiCache can store graphs but lacks native graph query capabilities.
Amazon DynamoDB
Why it's wrong here
DynamoDB is not efficient for graph traversals.
Amazon Neptune
Why this is correct
Neptune is a graph database optimized for highly connected data and graph queries.
Related concept
Read the scenario before looking for a memorised answer.
Amazon RDS for MySQL
Why it's wrong here
RDS requires complex join queries for graph data, which are inefficient.
Common exam traps
The trap here is that candidates often choose DynamoDB for its scalability and low latency, overlooking that graph queries like 'mutual friends' require native graph traversal capabilities that DynamoDB's key-value model cannot efficiently provide.
Detailed technical explanation
Under the hood, Neptune uses a purpose-built storage engine that indexes vertices and edges for fast adjacency lookups, enabling O(1) traversal to immediate neighbors. For a 'mutual friends' query, a Gremlin traversal like `g.V(user1).both('follows').where(both('follows').hasId(user2))` executes in a single request, whereas a relational database would require multiple self-joins on a follow table, which degrades exponentially as the graph grows. In real-world scenarios, Neptune can handle billions of edges with millisecond latency for multi-hop traversals, making it suitable for social networks with millions of users.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Neptune — Amazon Neptune is a fully managed graph database service optimized for storing and querying highly connected data. It supports both property graph and RDF models, and it uses Gremlin or SPARQL to efficiently traverse relationships like 'mutual friends' in a social media application, making it the ideal choice for graph queries.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 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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