DEA-C01 Data Store Management Practice Question
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?
⚠ Common exam trap
It's easy for candidates to confuse ElastiCache for Redis as a primary data store due to its low latency, overlooking that it is an in-memory cache with no built-in persistence guarantees, whereas DynamoDB provides both low latency and durable, persistent storage for JSON documents.
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
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.
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 DynamoDB
Why this is correct
DynamoDB delivers consistent single-digit-millisecond latency for both reads and writes at any scale, and its serverless, fully managed design pairs directly with Lambda. The stem's frequent updates and low-latency requirement rule out S3, which offers higher and more variable latency.
- ✗
Amazon ElastiCache for Redis
Why it's wrong here
ElastiCache for Redis is an in-memory cache, not a durable document store; it lacks the persistence guarantees and query model required for primary JSON storage. It is tempting because it delivers sub-millisecond latency, and would be correct as a caching layer in front of the actual datastore.
- ✗
Amazon S3 (with S3 Select)
Why it's wrong here
S3 Select filters objects at retrieval but S3 is an object store with eventual overwrite semantics, so frequent in-place document updates and single-digit-millisecond read/write latency are not achievable. It is tempting as a low-cost JSON repository, and would be correct for infrequent analytics over large static datasets.
- ✗
Amazon RDS for MySQL
Why it's wrong here
RDS for MySQL stores relational rows, not native JSON documents, and its connection overhead and storage engine do not deliver consistent single-digit-millisecond key-value latency for serverless workloads. It is tempting because RDS is a managed database, and would suit structured transactional data with SQL query requirements.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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