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DP-900 Practice Question: Describe considerations for working with non-relational data on Azure

You need to store a collection of JSON documents that contain user profile data. The data is frequently queried by user ID and by email address. The solution must support indexing on multiple fields and provide low-latency queries. 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 Cosmos DB

Azure Cosmos DB is a NoSQL database that supports indexing on multiple fields and provides low-latency queries on JSON documents. Option A is wrong because Azure Table Storage is a key-value store with limited indexing (only on partition key and row key). Option B is wrong because Azure Cache for Redis is an in-memory cache, not a durable indexed store. Option D is wrong because Azure Blob Storage stores unstructured blobs and does not support indexing on document fields.

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

    Why it's wrong here

    Azure Table Storage is a NoSQL key-value store that indexes only on PartitionKey and RowKey, so querying on other JSON properties forces a full table scan. While it can store serialized JSON as a string property, it lacks a native JSON type and does not automatically index nested fields. This makes it unsuitable for flexible document queries on multiple fields, which is the core requirement for a collection of JSON documents.

  • Azure Cache for Redis

    Why it's wrong here

    Azure Cache for Redis is an in-memory data store designed for caching and transient state, not durable document storage. It does not persist data by default, and although the RedisJSON module can store JSON, querying across documents requires manual scans or client-side filtering because Redis has no declarative query language or secondary indexes on JSON fields. Thus, it cannot serve as a primary indexed document store for low-latency queries on JSON property values.

  • Azure Cosmos DB

    Why this is correct

    Azure Cosmos DB is a globally distributed, multi-model database service with native support for JSON documents and automatic indexing of every property. Its index engine allows filtering, ordering, and joining on any field without pre-defining schemas or secondary indexes, ensuring low-latency queries even at scale. With tunable consistency levels and a SQL API, it is the ideal choice for a collection of JSON documents that require flexible querying and indexing on multiple fields.

  • Azure Blob Storage

    Why it's wrong here

    Azure Blob Storage is an object store for unstructured binary data such as images, videos, and backups; it treats a JSON file as an opaque block of bytes. There is no built-in index on the contents of a blob, so querying on JSON properties requires downloading and parsing every blob individually or building an external search index. This makes it inappropriate for document collections that demand direct, efficient queries on JSON fields.

Quick reference

Azure Blob Storage Tier Comparison

TierStorage CostRetrieval CostLatencyUse Case
HotHighestLowestImmediateActive data, frequent reads
CoolLowerHigherImmediateData accessed < once / month
ColdLower stillHigherImmediateData accessed < once / quarter
ArchiveLowestHighest + rehydration delayHoursLong-term compliance retention

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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.