AZ-204 Develop for Azure storage Practice Question
You need to store millions of small JSON documents (each ~1 KB) that are frequently updated by multiple concurrent users. You require low-latency access to individual documents. Which Azure Storage solution should you use?
⚠ Common exam trap
Test-takers frequently choose Azure Cosmos DB for NoSQL because it is a more feature-rich document database, but the question emphasizes cost-effectiveness and simplicity for high-volume, low-latency key-value access, which is exactly where Azure Table Storage excels.
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 Table Storage
Azure Table Storage is a NoSQL key-value store optimized for storing large volumes of structured, non-relational data with low-latency access by partition key and row key. It supports millions of small JSON documents (~1 KB) and handles frequent concurrent updates via optimistic concurrency control using ETags, making it ideal for this scenario.
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 with Block blobs
Why it's wrong here
Azure Blob Storage with Block blobs is generally optimized for storing large, unstructured binary data objects, typically greater than 1 MB, or for streaming data. Storing millions of small 1KB JSON documents as individual block blobs would incur significant transaction costs and overhead per object, leading to inefficient storage and retrieval due to the per-blob metadata and management. This approach is not cost-effective or performant for high-volume, small-entity storage scenarios requiring frequent access.
- ✓
Azure Table Storage
Why this is correct
Azure Table Storage is a highly scalable and cost-effective NoSQL key-value store specifically designed for storing massive quantities of structured, non-relational data. It excels at handling millions of small entities, like 1KB JSON documents, by leveraging PartitionKey and RowKey for efficient lookups and queries. Its design prioritizes low-cost storage and high throughput for simple data models, making it ideal for this scenario where cost-efficiency and scale for small documents are paramount.
- ✗
Azure Files with SMB protocol
Why it's wrong here
Azure Files with SMB protocol provides fully managed file shares in the cloud, primarily intended for lift-and-shift applications that require a file system interface or for sharing files across multiple virtual machines. It is not designed as a NoSQL document store and lacks the indexing and query capabilities necessary for efficient management of millions of individual 1KB JSON documents. Using it for this purpose would result in high latency, increased costs, and poor performance compared to a purpose-built NoSQL database.
- ✗
Azure Cosmos DB for NoSQL
Why it's wrong here
Azure Cosmos DB for NoSQL offers a globally distributed, multi-model database service with guaranteed low latency and high availability, making it suitable for mission-critical applications. However, for a scenario focused solely on cost-effectively storing millions of small 1KB JSON documents without requiring its advanced features like global distribution, multi-master writes, or specific API compatibility, Cosmos DB is significantly more expensive than Azure Table Storage. Its provisioned throughput model (RUs) would incur higher costs for simple storage and retrieval compared to Table Storage's optimized pricing for massive scale.
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