DP-203 Design and implement data storage Practice Question
You are designing a data storage solution for a retail company. The data includes transactional data that requires low-latency queries (under 10 milliseconds) and large historical data for analytics. The solution must minimize storage costs. Which approach should you recommend?
⚠ Common exam trap
A common mix-up: candidates assume a single service like Azure SQL Database or Data Lake Storage can handle both transactional and analytical workloads efficiently, overlooking the cost and performance trade-offs that make a hybrid approach optimal.
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
✓
Use Azure Cosmos DB for transactional data and Azure Blob Storage for historical data
Azure Cosmos DB provides single-digit millisecond latency for transactional workloads, meeting the under-10ms requirement, while Azure Blob Storage offers low-cost storage for large historical data. This combination minimizes storage costs by using the most cost-effective service for each workload type.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure Data Lake Storage Gen2 for both transactional and historical data
Why it's wrong here
Data Lake Storage Gen2 is object storage, so it cannot deliver sub-10-millisecond transactional query latency for the retail transactional workload. It is tempting because it cheaply holds massive historical analytics data, making it the right choice when the requirement is analytics-only storage with no low-latency transactional access.
- ✗
Use Azure Cache for Redis for transactional data and Azure SQL Database for historical data
Why it's wrong here
Azure SQL Database cannot guarantee sub-10-millisecond latency and its storage pricing does not minimise cost for large historical volumes. Redis is tempting for its low-latency caching, but it is the correct choice for session or hot-data caching, not as the transactional system of record.
- ✓
Use Azure Cosmos DB for transactional data and Azure Blob Storage for historical data
Why this is correct
Azure Cosmos DB delivers single-digit-millisecond reads for the transactional workload, satisfying the sub-10 ms latency constraint, while Azure Blob Storage's low-cost tiers hold the large historical dataset cheaply. Splitting hot and cold data this way minimises overall storage spend without compromising query performance.
- ✗
Use Azure SQL Database with Hyperscale tier for both transactional and historical data
Why it's wrong here
Hyperscale storage bills per provisioned compute and retained data, so keeping large historical analytics volumes there inflates cost rather than minimising it. It is tempting because Hyperscale genuinely delivers sub-10ms transactional latency and rapid scale, making it the right pick when a single relational database must serve both workloads without cost constraints.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-203 practice question is part of Courseiva's free Microsoft 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 DP-203 exam.