Quick Answer
The answer is Amazon DynamoDB with a global secondary index on the tag attribute, because this design directly supports flexible schema document management and efficient tag queries without rigid schema constraints. DynamoDB’s ability to store each document as an item with a list or set of tags, combined with a global secondary index that indexes each tag value, allows you to query by any single tag instantly; for queries involving multiple tags, you perform application-side intersection of the results from the index. On the AWS Certified Database Specialty DBS-C01 exam, this scenario tests your understanding of when to use NoSQL over relational or graph databases—a common trap is choosing RDS with join tables, which fails at 50 million documents due to join overhead, or Neptune, which is overkill for simple tag lookups. Remember the memory tip: “GSI on tags, intersect in app” to avoid complex joins and keep queries fast at scale.
This DBS-C01 practice question tests your understanding of workload-specific database design. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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 building a document management system where each document can have multiple tags and users need to query documents by any combination of tags. The number of tags per document is up to 20, and the total number of documents is expected to be 50 million. Which database design is most appropriate for this flexible tag-based querying?
Amazon DynamoDB with a global secondary index on the tag attribute
DynamoDB scales easily and supports flexible tag queries.
Amazon RDS for MySQL with a normalized schema
Why wrong: Joins on millions of documents can be slow.
Amazon Neptune
Why wrong: Neptune is overkill for simple tag-based queries.
Amazon ElastiCache for Memcached
Why wrong: Memcached is a cache, not a persistent data store.
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 DynamoDB with a global secondary index on the tag attribute
Amazon DynamoDB with a global secondary index on the tag attribute allows efficient querying by tag. To query multiple tags, application-side intersection is needed. Option A (RDS with multiple join tables) is wrong because it introduces complex joins and is less scalable. Option C (ElastiCache) is wrong because it is not a persistent database for primary storage. Option D (Neptune) is wrong because although graph databases can handle tags, they are not the most straightforward for simple tag queries.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon DynamoDB with a global secondary index on the tag attribute
Why this is correct
DynamoDB scales easily and supports flexible tag queries.
Related concept
Static NAT maps one inside address to one outside address.
Amazon RDS for MySQL with a normalized schema
Why it's wrong here
Joins on millions of documents can be slow.
Amazon Neptune
Why it's wrong here
Neptune is overkill for simple tag-based queries.
Amazon ElastiCache for Memcached
Why it's wrong here
Memcached is a cache, not a persistent data store.
Common exam traps
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
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
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DBS-C01 NAT questions on configuration and troubleshooting.
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FAQ
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Static NAT maps one inside address to one outside address..
The correct answer is: Amazon DynamoDB with a global secondary index on the tag attribute — Amazon DynamoDB with a global secondary index on the tag attribute allows efficient querying by tag. To query multiple tags, application-side intersection is needed. Option A (RDS with multiple join tables) is wrong because it introduces complex joins and is less scalable. Option C (ElastiCache) is wrong because it is not a persistent database for primary storage. Option D (Neptune) is wrong because although graph databases can handle tags, they are not the most straightforward for simple tag queries.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DBS-C01 NAT questions on configuration and troubleshooting.
Static NAT maps one inside address to one outside address.
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Same concept, more angles
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A startup is building a mobile app that requires a scalable NoSQL database. The data model includes user profiles with variable attributes that change over time. The database must support high read throughput and low latency. Which AWS database is best suited?
easyWhy C: Amazon DynamoDB is a fully managed NoSQL key-value and document database that delivers single-digit millisecond latency at any scale. It supports flexible schema with variable attributes, making it ideal for user profiles that change over time, and its provisioned or on-demand capacity modes enable high read throughput with consistent low latency.
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Last reviewed: Jun 20, 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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