Describe considerations for working with non-relational data on Azure →easyMultiple ChoiceObjective-mapped
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
You need to store event data from multiple sources in a schema-less format for later analysis. The data arrives as JSON and must be durable and highly available. Which Azure service should you use?
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 Blob Storage
Azure Blob Storage provides durable, highly available storage for JSON blobs with schema-less format. Option B is wrong because Azure SQL Database requires a schema. Option C is wrong because Azure Event Hubs is for ingestion, not long-term storage. Option D is wrong because Azure Data Factory is an orchestration service.
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 Blob Storage
Why this is correct
Azure Blob Storage is the correct option because it is a durable, massively scalable object storage service that can hold event data from any number of sources in its native format, such as JSON, Avro, or CSV, without requiring a predefined schema. It supports schema-on-read, meaning the structure can be inferred or defined later during analysis, and it integrates with Azure Data Lake Gen2 for big data workloads. Storing raw events in Blob Storage also preserves them for long-term retention, auditing, and reprocessing, which is exactly what this scenario requires.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is not appropriate because it is a relational database that requires a rigid, predefined schema, forcing you to define tables and columns before any data is inserted. Event data arriving from multiple sources often has inconsistent or evolving structures, which conflicts with this schema-on-write approach. Even if the data could be forced into tables, doing so would require significant up-front transformation and mapping, undermining the goal of quickly storing raw events as they arrive.
- ✗
Azure Event Hubs
Why it's wrong here
Azure Event Hubs is a lightweight real-time streaming ingestion service that temporarily buffers incoming events for consumption, not a durable storage solution. Its default retention window is only up to seven days, after which events are automatically purged, so it cannot serve as the long-term store for event data. It is best used as a front door to move events quickly into a data lake or analytical engine, but the actual storage goal must be handled by a service like Azure Blob Storage.
- ✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is an integration and orchestration service used to build ETL/ETL pipelines that copy, transform, or move data between connected systems, not a storage platform. It does not retain the event data itself; instead, it defines activities and triggers that determine when and how data is transferred from a source to a destination. Selecting Data Factory would be like choosing the delivery vehicle rather than the warehouse, so it cannot fulfill the requirement of storing event data.
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
Data Roles and Core Concepts
Key term
Schema
A schema is a blueprint or logical structure that defines how data is organized, stored, and accessed in a database or information system.
Key term
Blob storage
Blob storage is a cloud service for storing large amounts of unstructured data, such as text or binary data, like documents, images, and videos.
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