DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
You need to store JSON documents that are frequently read and written by a web application. Each document is about 10 KB. The solution must provide low-latency access globally. Which Azure data store 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 Cosmos DB
Azure Cosmos DB (option A) is correct because it is a globally distributed, multi-model database designed for low-latency reads and writes at any scale, and it natively supports JSON documents through its Core (SQL) API, making it ideal for a web application storing ~10 KB JSON documents with worldwide access. Its multi-region replication and single-digit-millisecond latency guarantees directly satisfy the global low-latency requirement. Azure Blob Storage (B) is object storage optimized for large unstructured blobs, not for frequent low-latency document reads/writes with querying. Azure SQL Database (C) is a relational engine that can store JSON but is not globally distributed for low-latency access and is less suited to schema-flexible document workloads. Azure Table Storage (D) is a key-value NoSQL store with limited querying and no multi-region low-latency replication comparable to Cosmos DB.
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 Cosmos DB
Why this is correct
Azure Cosmos DB stores JSON natively and offers single-digit-millisecond latency with global distribution across regions, meeting the low-latency worldwide requirement for 10 KB documents. Azure SQL Database and Blob storage cannot match that global read-write latency profile.
- ✗
Azure Blob Storage
Why it's wrong here
Blob Storage lacks native document querying and per-item indexing; it is object storage for unstructured blobs, not low-latency keyed reads of many small JSON documents. It would be correct for storing large files, backups or static web assets, where whole-object retrieval suffices.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database stores relational rows, requiring the JSON to be shredded or queried via JSON functions, and its geo-replication adds latency and cost rather than native global document access. It is the right choice for transactional relational data with strict schema and ACID guarantees.
- ✗
Azure Table Storage
Why it's wrong here
Table Storage stores entities as key-attribute pairs, not arbitrary nested JSON documents, and its single-region design does not deliver the required global low-latency reads. It suits cheap, high-volume structured key-value data accessed within one region, not globally distributed document workloads.
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
Azure Table Storage and Blob Data
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Table
A table is a structured collection of data organized into rows and columns, used in databases and spreadsheets to store and manage information efficiently.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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