DEA-C01 Data Store Management Practice Question
A data engineer must choose a storage service for a new application that requires single-digit millisecond latency at any scale, a flexible schema, and automatic scaling of throughput without provisioning capacity. The access pattern is key-value lookups by user ID with occasional range queries on a sort key. Which AWS service should the engineer select?
⚠ Common exam trap
The trap here is assuming a relational database such as Amazon RDS or a warehouse such as Redshift can deliver single-digit millisecond latency at any scale, when that guarantee belongs to DynamoDB's key-value design.
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 DynamoDB with on-demand capacity mode
DynamoDB is purpose-built for key-value and document workloads needing consistent single-digit millisecond latency at any scale. A partition key on user ID serves point lookups, and a sort key supports efficient range queries. On-demand capacity mode removes provisioning and scales automatically with traffic, while the flexible schema accommodates evolving attributes without migrations, matching every stated requirement.
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 RDS for PostgreSQL with automatic storage scaling
Why it's wrong here
RDS for PostgreSQL is a relational database that supports key-value access, but it requires choosing and managing instance classes, and throughput does not scale automatically with demand. Single-digit millisecond latency at any scale is not guaranteed under heavy concurrent load, and the engineer would need to provision read replicas or larger instances, adding operational effort.
- ✗
Amazon S3 with S3 Select
Why it's wrong here
S3 is object storage designed for high durability and throughput, not single-digit millisecond key-value access. S3 Select filters object contents but still requires scanning objects and cannot serve point lookups by user ID with consistent low latency. It also lacks a native sort key or automatic throughput scaling for transactional workloads, so it does not fit the access pattern.
- ✗
Amazon Redshift with a distribution key on user ID
Why it's wrong here
Redshift is a columnar data warehouse optimized for analytical queries over large datasets, not low-latency transactional key-value lookups. It requires provisioned or serverless compute and is not designed for single-digit millisecond point reads. A distribution key helps parallelize analytical scans, but the engine and storage model are a poor fit for high-volume user ID lookups.
- ✓
Amazon DynamoDB with on-demand capacity mode
Why this is correct
DynamoDB delivers consistent single-digit millisecond latency at any scale, supports a flexible schema with a partition key and optional sort key, and on-demand capacity mode scales read and write throughput automatically without provisioning. Key-value lookups by user ID map to the partition key, and range queries map to the sort key, matching the access pattern exactly.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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