Quick Answer
Amazon DynamoDB is the correct choice because it is purpose-built as both a key-value and document database, delivering single-digit millisecond latency at any scale, which directly matches the requirement for storing JSON documents accessed via a key-value pattern. DynamoDB’s internal architecture uses SSD-backed storage and distributed hash tables to maintain consistent low latency regardless of data volume, making it ideal for high-throughput workloads where performance must not degrade as the dataset grows. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your ability to distinguish DynamoDB from relational, graph, and MongoDB-compatible services—common traps include selecting Amazon DocumentDB for JSON storage, but DocumentDB does not guarantee the same latency at extreme scale, while RDS and Neptune serve entirely different data models. A reliable memory tip is to associate “key-value” and “any scale” directly with DynamoDB, and remember that DynamoDB’s “DAX” (DynamoDB Accelerator) further cements its microsecond-to-millisecond latency promise for cached reads.
This DEA-C01 practice question tests your understanding of data store management. 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 data engineer needs to store JSON documents that are accessed by a key-value pattern. The workload requires single-digit millisecond latency at any scale. Which AWS service is most appropriate?
Amazon DocumentDB (with MongoDB compatibility)
Why wrong: MongoDB compatible but not as fast for key-value patterns.
Amazon RDS for PostgreSQL
Why wrong: Relational, not key-value optimized.
Amazon DynamoDB
Key-value and document store with consistent low latency.
Amazon Neptune
Why wrong: Graph database, not key-value.
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
Amazon DynamoDB is a key-value and document database that provides single-digit millisecond latency at any scale. RDS is relational, Neptune is graph, and DocumentDB is MongoDB compatible but may not guarantee same latency at extreme scale.
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 DocumentDB (with MongoDB compatibility)
Why it's wrong here
MongoDB compatible but not as fast for key-value patterns.
Amazon RDS for PostgreSQL
Why it's wrong here
Relational, not key-value optimized.
Amazon DynamoDB
Why this is correct
Key-value and document store with consistent low latency.
Related concept
Static NAT maps one inside address to one outside address.
Amazon Neptune
Why it's wrong here
Graph database, not key-value.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
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 DEA-C01 NAT questions on configuration and troubleshooting.
Data Store Management — study guide chapter
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FAQ
Data Store Management — This question tests Data Store Management — Static NAT maps one inside address to one outside address..
The correct answer is: Amazon DynamoDB — Amazon DynamoDB is a key-value and document database that provides single-digit millisecond latency at any scale. RDS is relational, Neptune is graph, and DocumentDB is MongoDB compatible but may not guarantee same latency at extreme scale.
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 DEA-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 company needs to store JSON documents that are accessed by a key-value pattern. The data is 500 GB and requires single-digit millisecond latency. Which AWS database is most suitable?
easyWhy B: Option C is correct because DynamoDB supports document store and key-value access with low latency. Option A is wrong because RDS is relational. Option B is wrong because Neptune is graph. Option D is wrong because Redshift is analytical.
Variation 2. A data engineer needs to store JSON documents that are accessed by a serverless application using AWS Lambda. The documents are frequently updated and need low latency (single-digit milliseconds) for read and write operations. Which AWS service should the engineer use?
easyWhy A: Amazon DynamoDB is a fully managed NoSQL key-value and document database that provides single-digit millisecond latency for read and write operations at any scale. It natively supports JSON documents, integrates directly with AWS Lambda via the AWS SDK, and handles frequent updates efficiently through its auto-scaling and on-demand capacity modes, making it ideal for serverless applications requiring low-latency data access.
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Last reviewed: Jun 20, 2026
This DEA-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 DEA-C01 exam.
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