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 ride-sharing application needs to store real-time GPS location updates from drivers and passengers. The data is ingested as key-value pairs where the key is the user ID and the value is a timestamped location. The application requires low-latency reads and writes for millions of concurrent users, and the data model is simple with no need for complex queries or joins. Which Azure NoSQL database API should be used for this workload?
⚠ Common exam trap
A common mix-up: candidates choose the SQL (Core) API because it is the most versatile and well-known, but they overlook that the Table API is specifically optimized for simple key-value workloads with lower latency and cost, as it avoids the overhead of document parsing and indexing for complex queries.
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 Table API
Azure Cosmos DB Table API is the correct choice because it provides a key-value store with low-latency reads and writes, ideal for high-throughput scenarios like real-time GPS updates. It supports a simple schema-less data model where each item is a key-value pair, and it offers single-millisecond latency at the 99th percentile for both reads and writes, meeting the requirement for millions of concurrent users without complex queries or joins.
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 Table API
Why this is correct
The Table API is designed for key-value storage with simple queries by partition key and row key, providing low-latency access at global scale. It is ideal for this type of high-throughput, simple data access pattern.
- ✗
Azure Cosmos DB SQL (Core) API
Why it's wrong here
Azure Cosmos DB SQL (Core) API stores documents in JSON and provides rich SQL-based querying, indexing, and stored procedures. For a real-time telemetry stream that only needs point reads/writes by partition key and row key, these advanced features are unnecessary overhead that increases request units and cost without improving performance. The Table API offers a simpler, more cost-efficient key-value model aligned with the access pattern.
When this WOULD be correct
If the application required complex queries (e.g., filtering by location range, aggregations) or needed to store JSON documents with varying schemas, the SQL (Core) API would be correct. For example, a real-time analytics dashboard querying GPS data with filters and projections.
- ✗
Azure Cosmos DB for MongoDB API
Why it's wrong here
The MongoDB API is a document-oriented interface that emphasizes schema flexibility, allowing each document to have a different field structure. GPS location records have a flat, fixed schema (device ID, timestamp, latitude, longitude), so this flexibility is not beneficial; the document overhead—and the lack of a native key-value table abstraction—makes it less suitable for high-throughput location updates than the dedicated Table API.
When this WOULD be correct
A question where the application requires storing JSON documents with nested fields, needs to support ad-hoc queries and indexing on multiple properties, or requires compatibility with existing MongoDB drivers and ecosystems.
- ✗
Azure Cosmos DB for Apache Gremlin API
Why it's wrong here
The Gremlin API is a graph database engine designed to traverse relationships between entities, such as users and their social connections. Real-time GPS location writes are fundamentally simple key-value upserts (device ID → coordinates) with no need for relationship traversal, and modeling them as vertices/edges adds latency and complexity. Thus it is inappropriate.
When this WOULD be correct
A question describing a social network application that needs to analyze connections between users, such as finding friends of friends or recommending connections, where graph queries are essential.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The DP-900 exam frequently reuses these exact scenarios with slightly different constraints.
✓Azure Cosmos DB Table APICorrect answer▾
Why this is correct
The Table API is designed for key-value storage with simple queries by partition key and row key, providing low-latency access at global scale. It is ideal for this type of high-throughput, simple data access pattern.
✗Azure Cosmos DB SQL (Core) APIWrong answer — click to see why▾
Why this is wrong here
The SQL (Core) API supports complex queries and schema flexibility, but the question specifies a simple key-value data model with no need for complex queries or joins, making the Table API more appropriate due to its simpler key-value interface and lower overhead.
★ When this WOULD be the correct answer
If the application required complex queries (e.g., filtering by location range, aggregations) or needed to store JSON documents with varying schemas, the SQL (Core) API would be correct. For example, a real-time analytics dashboard querying GPS data with filters and projections.
Why candidates choose this
Candidates may assume the SQL (Core) API is the default or most capable option for any workload, overlooking that the Table API is optimized for simple key-value scenarios with lower latency and cost.
✗Azure Cosmos DB for MongoDB APIWrong answer — click to see why▾
Why this is wrong here
The MongoDB API is designed for document-oriented workloads with flexible schemas and complex queries, but the question specifies a simple key-value data model with no need for complex queries or joins. The Table API is more appropriate for such key-value scenarios.
★ When this WOULD be the correct answer
A question where the application requires storing JSON documents with nested fields, needs to support ad-hoc queries and indexing on multiple properties, or requires compatibility with existing MongoDB drivers and ecosystems.
Why candidates choose this
Candidates may associate MongoDB with high scalability and low latency for real-time data, but overlook that the Table API is optimized for simple key-value access patterns, which matches the described workload better.
✗Azure Cosmos DB for Apache Gremlin APIWrong answer — click to see why▾
Why this is wrong here
The Gremlin API is designed for graph databases to model complex relationships, but this scenario only requires simple key-value storage with no graph traversals or relationships.
★ When this WOULD be the correct answer
A question describing a social network application that needs to analyze connections between users, such as finding friends of friends or recommending connections, where graph queries are essential.
Why candidates choose this
Candidates may confuse 'real-time location updates' with graph data, thinking that tracking movements between locations requires graph capabilities, but the simple key-value model suffices.
Analysis generated from the official DP-900blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
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Related to this question
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Data Roles and Core Concepts
Key term
Data model
A data model is a blueprint that defines how data is organized, stored, and accessed in a database or data system.
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.