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Workload-Specific Database Design →easyMultiple ChoiceObjective-mapped

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 startup is building a social media application that needs to store user profiles, posts, comments, and likes. The data is highly interconnected, and the team wants to query relationships efficiently, such as 'find all friends of a user who liked a post'. Which database service is best suited for this workload?

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 optimized for highly interconnected data. It supports property graph and RDF models, enabling efficient traversal of relationships such as 'find all friends of a user who liked a post' using Gremlin or SPARQL queries. This makes it the ideal choice for social media applications requiring real-time relationship queries.

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 ElastiCache for Redis

    Why it's wrong here

    Redis is not a primary database for persistent storage.

  • ✗

    Amazon DynamoDB

    Why it's wrong here

    DynamoDB is not optimized for graph queries.

  • ✗

    Amazon RDS for PostgreSQL

    Why it's wrong here

    Relational databases can model graphs but are slower for multi-hop queries.

  • ✓

    Amazon Neptune

    Why this is correct

    Neptune is a graph database built for relationship queries.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The DBS-C01 exam often tests the misconception that a relational database (like PostgreSQL) can handle graph workloads efficiently via joins, but the trap is that relational databases suffer from exponential join complexity and lack native graph traversal optimizations, making Neptune the correct choice for deeply interconnected data.

Detailed technical explanation

How to think about this question

Neptune uses a graph storage engine that indexes vertices and edges separately, allowing constant-time traversal of relationships without expensive join operations. For example, a Gremlin query like `g.V().has('user', 'name', 'Alice').both('friends').out('likes').out('post')` executes as a single traversal across the graph, whereas in a relational database this would require multiple self-joins or recursive CTEs, degrading performance as depth increases. In real-world scenarios, Neptune can handle billions of relationships with millisecond latency for multi-hop queries, making it suitable for recommendation engines and social graphs.

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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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 optimized for highly interconnected data. It supports property graph and RDF models, enabling efficient traversal of relationships such as 'find all friends of a user who liked a post' using Gremlin or SPARQL queries. This makes it the ideal choice for social media applications requiring real-time relationship queries.

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

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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.