20+ practice questions focused on Describe considerations for working with non-relational data on Azure — one of the most tested topics on the Microsoft Azure Data Fundamentals DP-900 exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Describe considerations for working with non-relational data on Azure PracticeA global gaming company develops a multiplayer game. Player profile data (username, email, preferences) is stored as simple key-value pairs and must be accessible with single-digit millisecond latency from any region. Game session logs are stored as JSON documents with varying fields (session ID, player actions, timestamps) and must be queryable by player ID and timestamp range using SQL-like syntax. The company wants to use a single Azure database service for both workloads. Which combination of Azure Cosmos DB APIs should they choose?
Explanation: The Table API provides a simple key-value store ideal for low-latency profile lookups, while the SQL API supports querying JSON documents with SQL-like syntax, enabling efficient queries on game session logs by player ID and timestamp range. This combination meets both workloads using Azure Cosmos DB, but because each Cosmos DB account supports only one API, the profiles and logs would need to be stored in separate Cosmos DB accounts (one with Table API and one with SQL API).
A social networking application stores user profiles as JSON documents. Each profile can have different fields (e.g., education, work history, interests) depending on what the user fills in. The application also needs to traverse friend connections as a graph to recommend new friends. The development team wants to use a single Azure Cosmos DB account for both workloads. Which combination of Azure Cosmos DB APIs should they choose?
Explanation: A single Azure Cosmos DB account is provisioned with exactly one API. The Gremlin API stores data as vertices and edges with arbitrary properties, allowing it to handle flexible JSON-like profiles while also supporting Gremlin traversal queries for friend recommendations. The SQL API cannot perform Gremlin graph traversals, and the MongoDB/Table APIs lack graph support. Thus, option C is correct.
A social media platform stores user profiles as JSON documents where each profile can have different attributes (e.g., education, work history, interests). The platform also needs to traverse friend connections to recommend new connections using graph queries. The development team wants to use a single Azure Cosmos DB account for both workloads while minimizing complexity. Which combination of Azure Cosmos DB APIs should they choose?
Explanation: The Gremlin API supports both graph traversal (for friend connections) and document storage (user profiles as JSON documents in vertex properties) within a single API. Using only the Gremlin API in one Azure Cosmos DB account minimizes complexity, as a single account cannot host multiple APIs. Options A, B, and C are incorrect because they require combining two different APIs in one account, which is not supported—each Azure Cosmos DB account is tied to a single API.
A social media application stores user posts as JSON documents. Each post contains fields like post_id, author, content, and timestamp. The application needs to query posts by author and date range using SQL-like queries. Additionally, the application requires the ability to traverse follower relationships as a graph to suggest new friends. The development team wants to use a single Azure Cosmos DB account to minimize management overhead. Which combination of Azure Cosmos DB APIs should they choose?
Explanation: Azure Cosmos DB accounts are locked to a single API at creation. It is not possible to have both SQL and Gremlin APIs within the same account. To satisfy both document query and graph traversal requirements, separate Cosmos DB accounts must be used—one with the SQL API for posts and another with the Gremlin API for the follower graph. None of the provided options achieve this with a single account.
A logistics company stores shipment tracking data as JSON documents in Azure Cosmos DB. Each document contains fields like trackingId, origin, destination, status, weight, and optional fields (estimatedDelivery, carrierNotes). The application needs to perform low-latency lookups by trackingId and also run queries to find all shipments that have a specific origin and status. Which Azure Cosmos DB API should they choose?
Explanation: The SQL (Core) API is the best choice because it provides native support for querying JSON documents with a SQL-like syntax, enabling efficient low-latency lookups by trackingId (using a partition key) and flexible queries on fields like origin and status. It also supports indexing on any JSON property, making queries on optional fields like estimatedDelivery or carrierNotes performant without schema management.
+15 more Describe considerations for working with non-relational data on Azure questions available
Practice all Describe considerations for working with non-relational data on Azure questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Describe considerations for working with non-relational data on Azure. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Describe considerations for working with non-relational data on Azure questions on the DP-900 frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Describe considerations for working with non-relational data on Azure is tested as part of the Microsoft Azure Data Fundamentals DP-900 blueprint. Practicing with targeted Describe considerations for working with non-relational data on Azure questions ensures you can handle any format or difficulty that appears.
Yes. Courseiva provides free DP-900 practice questions across all exam topics and domains. The platform includes topic-based practice, mock exams, missed-question review, bookmarked questions, and readiness tracking — no account required.
Difficulty is subjective, but Describe considerations for working with non-relational data on Azure is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
Launch a full Describe considerations for working with non-relational data on Azure practice session with instant scoring and detailed explanations.
Start Describe considerations for working with non-relational data on Azure Practice →