Quick Answer
The correct answers are Amazon DynamoDB Accelerator (DAX), Amazon ElastiCache for Redis, and Amazon DynamoDB itself, because this combination directly addresses the need for sub-millisecond read and write latency in a real-time analytics workload accessed via a REST API. DynamoDB provides a fast, scalable NoSQL foundation, while DAX acts as an in-memory cache that reduces DynamoDB response times from single-digit milliseconds to microseconds for read-heavy operations. ElastiCache for Redis further supports this low-latency real-time analytics pattern by offering a fully managed, in-memory data store that can handle both reads and writes with consistent sub-millisecond performance, and its data structures are ideal for real-time aggregations and session management. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your ability to layer caching services for performance optimization—a common trap is choosing only DynamoDB without its accelerator, forgetting that DAX is specifically designed for read-heavy, latency-sensitive use cases. Remember the memory tip: “DynamoDB for the disk, DAX for the cache, Redis for the speed.”
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 is designing a data store for a real-time analytics application that requires sub-millisecond read and write latency. The data is accessed via a REST API. Which AWS services should the engineer consider? (Choose THREE.)
Amazon S3
Why wrong: S3 has higher latency (tens of milliseconds).
Amazon RDS for MySQL
Why wrong: RDS typically has higher latency and is not designed for sub-millisecond access.
Amazon ElastiCache for Redis
Redis provides sub-millisecond latency.
Amazon DynamoDB
DynamoDB provides single-digit millisecond latency.
DynamoDB Accelerator (DAX)
DAX provides sub-millisecond caching for DynamoDB.
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 ElastiCache for Redis
Amazon ElastiCache for Redis is correct because it provides an in-memory data store that delivers sub-millisecond read and write latency, ideal for real-time analytics. Redis supports data structures like strings, hashes, and sorted sets, and can be accessed via REST API through a caching layer or directly with Redis commands. This makes it suitable for low-latency, high-throughput workloads where disk-based storage would introduce unacceptable delays.
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 S3
Why it's wrong here
S3 has higher latency (tens of milliseconds).
Amazon RDS for MySQL
Why it's wrong here
RDS typically has higher latency and is not designed for sub-millisecond access.
Amazon ElastiCache for Redis
Why this is correct
Redis provides sub-millisecond latency.
Related concept
Read the scenario before looking for a memorised answer.
Amazon DynamoDB
Why this is correct
DynamoDB provides single-digit millisecond latency.
Related concept
Read the scenario before looking for a memorised answer.
DynamoDB Accelerator (DAX)
Why this is correct
DAX provides sub-millisecond caching for DynamoDB.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates may overlook DAX as a separate service and assume DynamoDB alone provides sub-millisecond latency, but DynamoDB's base latency is typically 1-10 milliseconds for strongly consistent reads, and DAX is required to achieve sub-millisecond performance for read-heavy workloads.
Detailed technical explanation
ElastiCache for Redis achieves sub-millisecond latency by storing all data in RAM and using an event-driven, single-threaded reactor model that processes commands without disk I/O. In real-time analytics, Redis can be used as a primary data store for leaderboards or session stores, but careful memory management is required because data loss can occur if persistence (e.g., AOF or RDB snapshots) is not configured. DynamoDB with DAX extends this by providing a fully managed, in-memory cache that offloads read traffic from DynamoDB's SSD-based storage, reducing p99 latencies from single-digit milliseconds to microseconds for cached items.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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
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FAQ
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon ElastiCache for Redis — Amazon ElastiCache for Redis is correct because it provides an in-memory data store that delivers sub-millisecond read and write latency, ideal for real-time analytics. Redis supports data structures like strings, hashes, and sorted sets, and can be accessed via REST API through a caching layer or directly with Redis commands. This makes it suitable for low-latency, high-throughput workloads where disk-based storage would introduce unacceptable delays.
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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Variation 1. A data engineer is designing a data store for a real-time analytics application that requires sub-millisecond read and write latency. The data is key-value in nature and the workload is both read-heavy and write-heavy. Which AWS service is most suitable?
easyWhy B: Amazon DynamoDB is the most suitable service because it is a fully managed NoSQL key-value and document database designed for single-digit millisecond latency at any scale, and with features like DynamoDB Accelerator (DAX) it can achieve sub-millisecond read latency. It supports both read-heavy and write-heavy workloads through its distributed architecture and auto-scaling capabilities, making it ideal for real-time analytics applications.
Last reviewed: Jun 24, 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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