This AZ-204 practice question tests your understanding of develop for azure storage. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You need to store millions of small JSON documents (each less than 1 KB) that are accessed by key. The data is read-heavy and requires low-latency access. Which Azure storage solution should you use?
Azure Files
Why wrong: File share, not key-value store.
Azure Table Storage
Why wrong: Good for structured data, but higher latency than Cosmos DB.
Azure Cosmos DB
NoSQL database with low-latency key-value access.
Azure Blob Storage
Why wrong: Better for larger objects; not low-latency for many small reads.
Answer choices
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 is the correct choice because it provides single-digit millisecond latency for point reads by key, supports automatic indexing of JSON documents, and offers a globally distributed, multi-model database service. For millions of small JSON documents accessed by key in a read-heavy workload, Cosmos DB's throughput-provisioned model and consistency levels optimize for low-latency access at scale.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Azure Files
Why it's wrong here
File share, not key-value store.
Azure Table Storage
Why it's wrong here
Good for structured data, but higher latency than Cosmos DB.
Azure Cosmos DB
Why this is correct
NoSQL database with low-latency key-value access.
Related concept
Read the scenario before looking for a memorised answer.
Azure Blob Storage
Why it's wrong here
Better for larger objects; not low-latency for many small reads.
Common exam traps
The trap here is that candidates confuse Azure Table Storage's key-value nature with JSON document support, but Table Storage stores entities as flat rows with limited property types and no native JSON indexing, whereas Cosmos DB is purpose-built for JSON documents with automatic indexing and guaranteed low latency.
Detailed technical explanation
Under the hood, Cosmos DB uses a B-tree-based index on the partition key and a hash-based index for point reads, enabling O(1) lookup latency. The resource model uses Request Units (RUs) to provision throughput, and for read-heavy workloads, you can use a lower consistency level (e.g., eventual) to reduce RU consumption and latency. A real-world scenario is a user profile cache where each profile is a <1 KB JSON document accessed by user ID, requiring <10 ms latency across millions of users.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Develop for Azure storage — This question tests Develop for Azure storage — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Cosmos DB — Azure Cosmos DB is the correct choice because it provides single-digit millisecond latency for point reads by key, supports automatic indexing of JSON documents, and offers a globally distributed, multi-model database service. For millions of small JSON documents accessed by key in a read-heavy workload, Cosmos DB's throughput-provisioned model and consistency levels optimize for low-latency access at scale.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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