Describe considerations for working with non-relational data on Azure →mediumMultiple ChoiceObjective-mapped
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
A company develops an IoT device registry that stores device metadata as JSON documents. Each device has a unique DeviceID, and the attributes vary per device type (e.g., sensors, actuators). The application requires low-latency reads by DeviceID and needs global distribution to support devices worldwide. Which Azure Cosmos DB API should they choose to natively support JSON documents with flexible schema?
⚠ Common exam trap
Watch out — candidates often choose the MongoDB API because they associate JSON with MongoDB, but the SQL API is the native JSON document API in Cosmos DB and is the correct answer for 'natively support JSON documents with flexible schema' in the context of Azure Cosmos DB.
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 SQL API
The Azure Cosmos DB SQL API (formerly DocumentDB) is the correct choice because it provides native support for storing and querying JSON documents with flexible schema, allowing each device document to have a unique DeviceID and varying attributes per device type. It offers low-latency reads by DeviceID via direct point reads using the partition key, and supports global distribution through multi-region writes and automatic replication, meeting the worldwide deployment requirement.
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 SQL API
Why this is correct
The SQL API is the native JSON document model in Azure Cosmos DB, allowing devices to be stored as schemaless JSON documents with automatic indexing and rich querying via standard SQL syntax. It provides single-digit-millisecond point reads by ID, tunable consistency, and global distribution, making it ideal for an IoT device registry.
- ✗
Azure Cosmos DB Table API
Why it's wrong here
The Table API is a key-value store offering a fixed, non-relational schema that is identical to Azure Table Storage, so each device entity is a simple row with partition and row keys. It lacks the flexible JSON document structure and rich SQL query capabilities needed to model evolving device metadata effectively.
- ✗
Azure Cosmos DB for MongoDB API
Why it's wrong here
The MongoDB API represents Cosmos DB's implementation of the MongoDB wire protocol, which is beneficial for migrating existing MongoDB workloads. However, it does not offer the native SQL query engine or full Cosmos DB integration, and for a greenfield IoT registry, the SQL API would be the more direct choice for JSON document storage.
- ✗
Azure Cosmos DB Gremlin API
Why it's wrong here
The Gremlin API is designed for graph data modeling, where entities are nodes and relationships are edges, such as social networks or recommendation engines. An IoT device registry storing device metadata as JSON documents is not a graph problem, so this API would require an unnatural transformation of the data.
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Related to this question
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Azure SQL Services
Key term
DocumentDB
Amazon DocumentDB is a fully managed, MongoDB-compatible document database service that stores, queries, and indexes JSON-like data for scalable applications.
Key term
Schema
A schema is a blueprint or logical structure that defines how data is organized, stored, and accessed in a database or information system.
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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.