Describe considerations for working with non-relational data on Azure →hardMultiple ChoiceObjective-mapped
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
A global social media platform stores user profile images (JPEG) and activity logs in JSON format. The logs have varying structures based on the type of activity. The application requires low-latency reads of images from any region and the ability to query logs using SQL-like syntax. Which Azure data storage solution should they use for each data type?
⚠ Common exam trap
Watch out — candidates often confuse Azure Table Storage (key-value) with Cosmos DB Table API, or assume Azure SQL Database can handle JSON logs via OPENJSON, but the question explicitly requires SQL-like syntax for varying structures, which Cosmos DB SQL API handles natively without schema enforcement.
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 with a CDN for images and Azure Cosmos DB (SQL API) for logs
Azure Blob Storage is optimized for storing large binary objects like JPEG images, and integrating it with Azure CDN ensures low-latency reads globally by caching content at edge nodes. Azure Cosmos DB with the SQL API provides native support for querying JSON documents with varying schemas using SQL-like syntax, making it ideal for the activity logs.
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 for images and Azure Cosmos DB (Table API) for logs
Why it's wrong here
Azure Table Storage is a structured NoSQL key-value store that stores entities with defined properties, not large binary files; storing JPEG images there would be inefficient and eventually hit row size limits. For logs, Cosmos DB with the Table API provides only key-value access with limited query ability—it does not support SQL-like queries, which the requirement explicitly specifies. The SQL API, by contrast, offers full query flexibility over JSON documents. Thus, this option inadequately handles both image storage and log querying.
When this WOULD be correct
A question requiring key-value storage for structured data (e.g., user preferences) with no need for SQL queries, and a separate need for storing small, frequently accessed blobs without global low-latency requirements.
- ✓
Azure Blob Storage with a CDN for images and Azure Cosmos DB (SQL API) for logs
Why this is correct
Azure Blob Storage is purpose-built for storing unstructured binary data like JPEG images, offering massive scalability and low cost per gigabyte. Pairing it with Azure CDN caches image copies at edge locations worldwide, dramatically reducing latency for global users. Azure Cosmos DB's SQL API stores each log entry as a JSON document and supports querying with familiar SQL-like syntax, accommodating the variable structure of the logs without requiring a predefined schema. This combination directly satisfies the requirements for unstructured image storage and flexible, queryable log storage.
- ✗
Azure Files for images and Azure SQL Database for logs
Why it's wrong here
Azure Files offers managed SMB/NFS file shares for legacy applications and file-based workflows, not designed for serving static images to millions of users globally—it lacks a built-in CDN and object-level access patterns. Azure SQL Database is a relational database requiring a fixed schema, so every log entry must conform to pre-defined columns, which conflicts with the varying JSON log structure. This makes storing schema-less logs cumbersome and forces costly schema migrations or generic columns. This combination mismatches both requirements.
When this WOULD be correct
For a scenario requiring shared file access across multiple VMs using SMB protocol for images, and structured relational data with fixed schema for logs that need complex joins and transactions.
- ✗
Azure Disk Storage for images and Azure Cosmos DB (MongoDB API) for logs
Why it's wrong here
Azure Disk Storage is unsuitable for global low-latency image reads as it provides persistent storage for virtual machines, not a distributed object store for direct application access. For logs, Azure Cosmos DB with the MongoDB API does not natively offer SQL-like querying, which the requirement specifies. This option is tempting because Disk Storage provides high-performance VM storage, and Cosmos DB handles varying JSON schemas well, making it ideal if MongoDB query language was acceptable or images were VM-attached.
When this WOULD be correct
A question requiring high-performance disk I/O for a VM-based application (e.g., a database server) and document storage with MongoDB compatibility (e.g., a MongoDB migration) would make this option correct.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The DP-900 exam frequently reuses these exact scenarios with slightly different constraints.
✓Azure Blob Storage with a CDN for images and Azure Cosmos DB (SQL API) for logsCorrect answer▾
Why this is correct
Azure Blob Storage is purpose-built for storing unstructured binary data like JPEG images, offering massive scalability and low cost per gigabyte. Pairing it with Azure CDN caches image copies at edge locations worldwide, dramatically reducing latency for global users. Azure Cosmos DB's SQL API stores each log entry as a JSON document and supports querying with familiar SQL-like syntax, accommodating the variable structure of the logs without requiring a predefined schema. This combination directly satisfies the requirements for unstructured image storage and flexible, queryable log storage.
✗Azure Table Storage for images and Azure Cosmos DB (Table API) for logsWrong answer — click to see why▾
Why this is wrong here
Azure Table Storage is not optimized for low-latency global reads of large binary files like JPEG images; Blob Storage with CDN is required. For logs with varying structures, Azure Cosmos DB SQL API supports SQL-like queries, but Table API does not offer SQL syntax.
★ When this WOULD be the correct answer
A question requiring key-value storage for structured data (e.g., user preferences) with no need for SQL queries, and a separate need for storing small, frequently accessed blobs without global low-latency requirements.
Why candidates choose this
Candidates may associate 'Table' with structured data and assume Table Storage can handle images, or think Table API supports SQL-like queries, confusing it with the SQL API.
✗Azure Files for images and Azure SQL Database for logsWrong answer — click to see why▾
Why this is wrong here
Azure Files provides SMB file shares, not optimized for low-latency global image delivery; Azure SQL Database is relational and not designed for semi-structured JSON logs with varying schemas.
★ When this WOULD be the correct answer
For a scenario requiring shared file access across multiple VMs using SMB protocol for images, and structured relational data with fixed schema for logs that need complex joins and transactions.
Why candidates choose this
Candidates may think Azure Files is suitable for storing images as files, and Azure SQL Database can handle JSON, but overlook the need for global low-latency image delivery and flexible schema for logs.
✗Azure Disk Storage for images and Azure Cosmos DB (MongoDB API) for logsWrong answer — click to see why▾
Why this is wrong here
Azure Disk Storage is designed for persistent block storage for VMs, not for serving images globally with low-latency reads. Azure Cosmos DB MongoDB API does not support SQL-like querying; it uses MongoDB queries, not SQL syntax.
★ When this WOULD be the correct answer
A question requiring high-performance disk I/O for a VM-based application (e.g., a database server) and document storage with MongoDB compatibility (e.g., a MongoDB migration) would make this option correct.
Why candidates choose this
Candidates may associate Azure Disk Storage with 'storage' broadly and think Cosmos DB's MongoDB API is similar to SQL, overlooking the specific requirements for global low-latency image access and SQL-like querying.
Analysis generated from the official DP-900blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
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
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.
Key term
Azure Cosmos DB
Azure Cosmos DB is a fully managed, globally distributed NoSQL database service that offers fast reads and writes anywhere in the world with automatic scaling and multiple consistency models.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-900 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-900 exam.