DP-203 Design and implement data storage Practice Question
A company is designing a data storage solution for IoT device telemetry. Each device sends a JSON payload every second. The data must be stored in a way that supports real-time dashboards and long-term analytics with low latency. Which Azure data store should be used for the ingestion layer?
⚠ Common exam trap
Many candidates confuse the ingestion layer with the storage layer, choosing Azure Blob Storage or Data Lake Storage because they think 'store data' means persistent storage, but the question specifically asks for the ingestion layer where real-time, low-latency streaming is required, which Event Hubs uniquely provides.
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 Event Hubs
Azure Event Hubs is the correct choice for the ingestion layer because it is a fully managed, real-time data streaming platform designed to ingest millions of events per second with low latency. It supports the capture of JSON telemetry from IoT devices and integrates directly with downstream analytics services like Azure Stream Analytics for real-time dashboards and long-term storage in Azure Data Lake or Blob Storage. Its partitioned throughput model ensures scalable, durable ingestion without blocking producers.
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 SQL Database
Why it's wrong here
Azure SQL Database is a relational engine with fixed schemas and row-store writes, so per-second JSON telemetry from many devices would bottleneck on transactional ingestion rather than scale-out append throughput. It suits structured OLTP workloads needing joins and constraints, not high-volume device event capture.
- ✗
Azure Blob Storage
Why it's wrong here
Azure Blob Storage accepts files but offers no native event-stream ingestion or low-latency query endpoint, so dashboards would poll stored blobs rather than consume live telemetry. It suits cheap archival and batch processing of already-captured data, not the ingestion layer itself.
- ✓
Azure Event Hubs
Why this is correct
Event Hubs ingests millions of telemetry events per second with low latency, buffering the stream for downstream consumers. This satisfies the real-time dashboard requirement while retaining data for long-term analytics, unlike batch-oriented stores such as Blob Storage or Azure SQL Database.
- ✗
Azure Data Lake Storage
Why it's wrong here
Azure Data Lake Storage is a batch-oriented object store; writes land as files with no native per-event streaming ingest or sub-second query serving, so real-time dashboards cannot read fresh telemetry directly. It fits landing and long-term analytical storage after events are captured elsewhere.
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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.