DP-900 Describe considerations for working with non-relational data on Azure Practice Test 6 — 15 Questions

Question 1

A social networking application stores user profiles as JSON documents in Azure Cosmos DB. Each profile includes fields such as 'userName', 'email', 'followersCount', and optional 'interests'. The application needs to perform fast point reads by 'userName' (under 10 ms) and also run queries to find all users with a 'followersCount' greater than a certain value. The development team prefers to use a query syntax similar to SQL. Which Azure Cosmos DB API should they choose?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Azure Cosmos DB for NoSQL (SQL API). Azure Cosmos DB for NoSQL (SQL API) is the correct choice because it natively supports SQL-like query syntax for querying JSON documents, enabling the required queries such as filtering by 'followersCount'. It also provides fast point reads (under 10 ms) by using the 'userName' field as the partition key, ensuring efficient direct access to individual documents.

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Azure Cosmos DB for MongoDB

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Azure Cosmos DB for Table

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Azure Cosmos DB for Apache Cassandra

Question 2

A smart city application collects sensor data from thousands of devices. Data is ingested as JSON messages containing deviceId, timestamp, and reading value. The application must support fast point reads by deviceId and also run queries to retrieve all readings for a specific deviceId within a time range. The development team prefers a SQL-like query language. Which Azure Cosmos DB API should they choose?

Accepted Answer

SQL (Core) API. The SQL (Core) API is the best choice because it natively supports SQL-like querying, enabling both fast point reads by deviceId (using the partition key) and efficient time-range queries on a specific deviceId. It also provides native JSON support, which aligns with the JSON message format from the sensors, and allows indexing on timestamp for range queries.

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Table API

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MongoDB API

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Cassandra API

Question 3

A social networking application uses Azure Cosmos DB to store user posts. When a user publishes a new post, they immediately refresh their feed and expect to see their own post. However, the application can tolerate temporary staleness for posts from other users (e.g., a few seconds delay). Which Azure Cosmos DB consistency level should the application use for read operations that display the feed?

Accepted Answer

Session. Session consistency is the correct choice because it guarantees that the user who writes a post will read their own write within the same session, while allowing other users to see slightly stale data. This matches the requirement: the author immediately sees their new post, but the application can tolerate a few seconds of staleness for other users' posts. Session consistency uses a session token to ensure monotonic reads and writes for the same client, making it ideal for per-user feed scenarios.

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Strong

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Bounded staleness

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Eventual

Question 4

A social networking application needs to store and query relationships between users, such as 'friends of friends' to recommend new connections. The application must traverse these relationships efficiently. Which Azure NoSQL data store and API should they choose?

Accepted Answer

Azure Cosmos DB with Gremlin API. Azure Cosmos DB with Gremlin API is correct because it provides a graph database model specifically designed for storing and querying highly connected data, such as user relationships. The Gremlin API supports graph traversal queries (e.g., 'friends of friends') natively using the Apache TinkerPop graph traversal language, enabling efficient navigation of edges and vertices without expensive join operations.

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Azure Cosmos DB with MongoDB API

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Azure Table Storage

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Azure Cosmos DB with SQL API

Question 5

A social media application stores user posts as JSON documents in Azure Cosmos DB. Each post includes fields such as postId, userId, content, timestamp, and an array of tags. The development team wants to query posts by userId and timestamp range using a SQL-like syntax. Which Azure Cosmos DB API should they choose?

Accepted Answer

B. Azure Cosmos DB for NoSQL API (Core SQL API). The Azure Cosmos DB for NoSQL API (Core SQL API) is the correct choice because it natively supports SQL-like querying (SELECT, WHERE, ORDER BY) over JSON documents. The team's requirement to query posts by userId and timestamp range using SQL-like syntax is directly supported by this API, which treats each JSON document as an item and allows filtering on nested fields like userId and timestamp. Other APIs either lack native SQL-like syntax or are optimized for different data models (e.g., MongoDB uses a JSON-like query language, Table API uses OData, Cassandra uses CQL).

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A. Azure Cosmos DB for MongoDB API

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C. Azure Cosmos DB for Table API

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D. Azure Cosmos DB for Apache Cassandra API

Question 6

A manufacturing company installs IoT sensors on equipment in a factory. Each sensor sends a reading (device ID, timestamp, temperature, vibration) every second. The application must store these readings with extremely low write latency, support queries for the latest reading per device, and allow range queries over the last hour for a specific device. The development team expects high throughput writes (millions per day) and does not require complex joins. Which Azure data store is most appropriate for this workload?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is the most appropriate because it offers single-digit millisecond write and read latencies at any scale, which is critical for the high-throughput, low-latency IoT sensor ingestion described. Its support for automatic indexing and efficient point reads (by device ID and timestamp) enables fast retrieval of the latest reading per device, while its native time-to-live (TTL) and range query capabilities on the timestamp field allow efficient queries over the last hour for a specific device. Additionally, Cosmos DB's schema-agnostic, non-relational model fits the simple key-value structure of sensor readings without requiring complex joins.

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Azure Table Storage

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Azure Blob Storage

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Azure SQL Database

Question 7

A company has a legacy application that requires SMB (Server Message Block) file shares to store and access configuration files. They want to migrate this data to Azure without modifying the application. Which Azure storage solution should they use?

Accepted Answer

Azure Files. Azure Files provides fully managed SMB (Server Message Block) file shares in the cloud, supporting the SMB 3.0 protocol. This allows the legacy application to access configuration files over the network using standard file share paths without any code changes, making it the ideal migration target for lift-and-shift scenarios.

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Azure Blob Storage

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Azure Queue Storage

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Azure Disk Storage

Question 8

A mobile game company stores player profiles and game state in Azure Cosmos DB. Each document contains playerId, level, score, inventory (an array of items), and lastLogin. The application requires fast point reads by playerId, queries to find all players within a specific score range, and global distribution with multi-region writes for low latency worldwide. They also want to use a familiar SQL-like query language. Which Azure Cosmos DB API should they choose?

Accepted Answer

Core (SQL) API. The Core (SQL) API is the correct choice because it provides native support for SQL-like queries, enabling the required point reads by playerId and range queries on score. It also offers multi-region writes for global distribution with low latency, which aligns with the application's need for worldwide player access. The document model with arrays (inventory) is directly supported, making it ideal for storing player profiles and game state.

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MongoDB API

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Cassandra API

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Gremlin API

Question 9

A manufacturing company stores IoT sensor data as blobs in Azure Blob Storage. Each blob is named with a device ID and a timestamp, and they need to quickly find all blobs for a specific device within a date range. Which Azure Blob Storage feature should they use to query blobs based on custom metadata?

Accepted Answer

Blob index tags. Blob index tags allow you to apply custom key-value metadata to blobs and then query them using a filtered query across containers or storage accounts. This enables efficient retrieval of blobs by device ID and timestamp without scanning all blob names or maintaining a separate index.

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Blob snapshots

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Blob soft delete

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Blob lifecycle management

Question 10

A retail company plans to store product catalog data that includes product ID, name, description, price, and a varying set of attributes (e.g., size, color, material). The application requires low-latency reads and writes, global distribution, and the ability to handle schema flexibility. Which Azure data store is best suited for this workload?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is the best choice because it provides low-latency reads and writes (single-digit milliseconds at the 99th percentile), global distribution with multi-region writes, and automatic schema flexibility through its document model. It supports varying product attributes (e.g., size, color, material) without requiring schema changes, and its turnkey global distribution ensures data is replicated across regions for fast access.

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Azure SQL Database

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Azure Table Storage

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Azure Blob Storage

Question 11

A media company stores raw video footage as blobs in Azure Blob Storage. After processing, the raw footage is kept for compliance purposes and is accessed only a few times per year. The company wants to minimize storage costs while ensuring the data is durable and can be restored within 24 hours if needed. Which Azure Blob Storage access tier should they use?

Accepted Answer

Archive. The Archive tier is the correct choice because it offers the lowest storage cost for data that is rarely accessed (a few times per year) and can tolerate a retrieval latency of up to 15 hours, which is well within the 24-hour restoration requirement. Azure Blob Storage's Archive tier is designed for long-term retention, compliance, and backup scenarios where durability is maintained through geo-redundant replication options, and data can be rehydrated to an online tier (e.g., Hot or Cool) within the specified time frame.

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Hot

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Cool

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Cold

Question 12

A startup develops a mobile application that stores user preferences as simple key-value pairs. The app is only used in North America, and the team needs low-latency reads and writes with minimal cost. They do not require global distribution or complex querying. Which Azure data store should they choose?

Accepted Answer

Azure Table Storage. Azure Table Storage is the correct choice because it provides a cost-effective, low-latency key-value store for simple data like user preferences, with no need for global distribution or complex querying. It offers single-digit millisecond latency for reads and writes within a single region, and its pay-per-request pricing model minimizes cost for a startup. The Table API in Azure Cosmos DB would be overkill and more expensive for this North America-only, non-distributed scenario.

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Azure Cosmos DB (SQL API)

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Azure Cosmos DB (Table API)

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Azure SQL Database

Question 13

A mobile gaming company stores player data in Azure Cosmos DB using the Core (SQL) API. Each document contains fields: playerId, nickname, score, level, and an inventory array of item objects (each with name and type). The company wants to query all players whose score is above 5000 and who have a specific item (e.g., a sword) in their inventory. Which query clause should they use?

Accepted Answer

B) WHERE c.score > 5000 AND ARRAY_CONTAINS(c.inventory, {name: 'sword'}, true). ARRAY_CONTAINS with the third parameter set to 'true' performs a partial match, checking if any element in the inventory array has a 'name' property equal to 'sword'. This is the standard way to query for an item within an array of objects in Azure Cosmos DB's SQL API, as it correctly handles the nested structure without requiring a JOIN or subquery.

Answer

A) WHERE c.score > 5000 AND c.inventory.some(item => item.name == 'sword')

Answer

C) WHERE c.score > 5000 AND c.inventory.name == 'sword'

Answer

D) WHERE c.score > 5000 AND 'sword' IN c.inventory

Question 14

A media publishing company stores high-resolution images and video files for their website. These files are large (hundreds of MBs each) and are accessed only a few times per month, but when accessed, they must be delivered within seconds. Additionally, they need to store a small amount of metadata (e.g., upload date, author) for each file. Which Azure service should they use for storing the binary files?

Accepted Answer

Azure Blob Storage. Azure Blob Storage is designed for storing massive amounts of unstructured binary data, such as high-resolution images and video files. It supports objects up to 4.75 TB in size, offers tiered storage (including cool and archive tiers) to optimize cost for infrequently accessed data, and provides low-latency access (typically under 10 seconds) for retrieval when needed. This makes it the ideal choice for the media publishing company's requirements.

Answer

Azure Table Storage

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Azure File Storage

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Azure Queue Storage

Question 15

A global social media platform allows users to like posts. The platform is designed to prioritize availability and partition tolerance over strong consistency across its globally distributed Azure Cosmos DB instance. When a user likes a post, the like count may not be immediately visible to all users, but it will eventually become consistent across all regions. Which consistency model does this application follow?

Accepted Answer

Eventual consistency. Eventual consistency is the correct choice because the platform prioritizes availability and partition tolerance (AP from the CAP theorem) over strong consistency. In Azure Cosmos DB, eventual consistency guarantees that all replicas will converge to the same value over time without any ordering guarantees, which matches the scenario where like counts are not immediately visible but become consistent eventually.

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Strong consistency

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Bounded staleness consistency

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Session consistency