DEA-C01 Data Store Management Practice Question
A company's analytics team needs a petabyte-scale, fully managed data warehouse that supports standard SQL, columnar storage, and massively parallel query execution, and it must integrate with existing business intelligence tools with minimal operational effort. Which AWS service should the data engineer choose?
⚠ Common exam trap
The trap here is being drawn to any highly scalable AWS data store and overlooking that only a columnar, MPP SQL warehouse satisfies the analytics and BI requirements.
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 Redshift
The workload calls for a managed analytical database with columnar storage, massively parallel execution, and standard SQL connectivity for BI tools. Amazon Redshift delivers all three as a managed service, so the team avoids building and operating its own warehouse. The other services target transactional NoSQL access, in-memory caching, or data movement rather than petabyte-scale SQL analytics.
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 Redshift
Why this is correct
Amazon Redshift is a fully managed, petabyte-scale data warehouse that uses columnar storage on a cluster of nodes with massively parallel processing, and it speaks standard SQL that BI tools connect to through JDBC and ODBC drivers. It matches every stated requirement, including minimal operational effort, because AWS handles provisioning, patching, and backups of the cluster.
- ✗
AWS Database Migration Service
Why it's wrong here
AWS Database Migration Service moves data between source and target databases; it is a replication and migration tool, not a place to store or query petabytes. It has no columnar storage, no MPP query engine, and no SQL endpoint for BI tools to connect to. Using it as the analytics platform would leave the company without any warehouse to query.
- ✗
Amazon ElastiCache for Redis
Why it's wrong here
ElastiCache for Redis is an in-memory data store used for caching, session management, and sub-millisecond lookups. It holds data in RAM, so it cannot cost-effectively retain or scan petabytes, and it does not provide SQL or columnar analytics. Choosing it would fail the scale and query-language requirements of the petabyte warehouse workload.
- ✗
Amazon DynamoDB
Why it's wrong here
DynamoDB is a serverless NoSQL key-value and document store designed for single-digit millisecond access at any scale, not for analytical SQL over petabytes. It lacks a columnar, MPP query engine and standard SQL support, so the BI tools and analytical workloads described cannot run against it without exporting data to another service. It solves transactional access patterns, not warehousing.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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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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