DP-203 Design and implement data storage Practice Question
You are designing a data storage solution for a marketing analytics platform. The platform collects clickstream data from websites and needs to store it for both real-time dashboards and historical analysis. The data is semi-structured (JSON) and arrives at a rate of 10,000 events per second. You need to choose an Azure storage solution that can handle the ingestion rate, support schema-on-read, and integrate with Azure Databricks for advanced analytics. The solution must also be cost-effective for long-term storage. What should you use?
⚠ Common exam trap
Candidates often choose Azure Cosmos DB for its real-time capabilities, overlooking that the question emphasizes cost-effective long-term storage and schema-on-read for historical analysis, which ADLS Gen2 handles far more efficiently and cheaply than Cosmos DB's per-request-unit pricing model.
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
✓
Azure Data Lake Storage Gen2
Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with Azure Blob Storage, providing high-throughput ingestion (up to 60 GB/s per account) to handle 10,000 events per second of semi-structured JSON data. It supports schema-on-read natively, allowing Azure Databricks to query the data directly using Spark without prior schema definition, and its tiered storage (hot, cool, archive) makes it cost-effective for long-term historical analysis.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Table Storage
Why it's wrong here
Table Storage lacks advanced analytics integration and schema-on-read flexibility.
- ✓
Azure Data Lake Storage Gen2
Why this is correct
ADLS Gen2 meets all requirements: high throughput, schema-on-read, Databricks integration, cost-effective.
- ✗
Azure Cosmos DB
Why it's wrong here
Cosmos DB is transaction-optimized and more expensive for large-scale analytics.
- ✗
Azure SQL Database
Why it's wrong here
SQL Database is not designed for high-velocity JSON ingestion at this scale.
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
Related to this question
Learn chapter
Introduction to Azure Data Engineering
Key term
Azure Data Lake Gen2
Azure Data Lake Gen2 is a cloud-based data storage service that combines the scalability and performance of a data lake with the hierarchical file system and security of a data warehouse, designed for big data analytics.
Key term
Azure Databricks
Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure that lets data teams prepare data, run machine learning models, and build data pipelines using a single workspace.
About these practice questions
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JA
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.