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

A company is developing a web application that stores user profiles as JSON documents. The application needs to query these documents using SQL-like queries, and must support automatic indexing of all properties. They want a fully managed, globally distributed NoSQL database with low latency. Which Azure Cosmos DB API should they use?

⚠ Common exam trap

Watch out — candidates often confuse the SQL API with the Table API because both support querying, but the Table API lacks SQL-like syntax and automatic indexing of all properties, making it unsuitable for JSON document workloads.

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

SQL API

The SQL API (formerly DocumentDB API) is the correct choice because it natively supports querying JSON documents with SQL-like syntax (SELECT * FROM c WHERE c.property = value). It automatically indexes all properties by default, provides a fully managed, globally distributed NoSQL database with low-latency reads and writes, and is designed specifically for document-based workloads like user profiles.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Table API

    Why it's wrong here

    The Table API in Azure Cosmos DB is a key-value and wide-column store that organizes data into tables with partition keys and row keys, not as free-form JSON documents. It supports OData-style queries instead of SQL-like JSON queries, and it does not automatically index arbitrary nested JSON properties. Therefore, while you could convert user profiles into table entities, the Table API cannot natively query the JSON documents themselves as documents.

  • Cassandra API

    Why it's wrong here

    The Cassandra API in Azure Cosmos DB is a compatibility layer for existing Cassandra applications, using the Cassandra Query Language (CQL) over a wide-column data model. Although CQL has some support for JSON-formatted inserts and selects, the data is ultimately mapped to a predefined, columnar table schema—it does not allow schema-free JSON document queries or the Cosmos DB SQL query engine. This makes it poorly suited for storing and querying heterogeneous JSON user profiles directly as documents.

  • SQL API

    Why this is correct

    The SQL API is the native document API for Azure Cosmos DB: it stores user profiles as full JSON documents in containers and queries them with a SQL-like syntax that understands JSON types, nested objects, and arrays. This API automatically indexes every property of the JSON document, enabling efficient filtering, projection, and joins without requiring a fixed schema. For a web application that needs to store and retrieve JSON user profiles as documents, the SQL API is the correct choice.

  • Gremlin API

    Why it's wrong here

    The Gremlin API in Azure Cosmos DB is intended for graph data models, where data is represented as vertices, edges, and properties and queried using the Gremlin graph traversal language. While a JSON user profile could theoretically be mapped to a vertex's properties, the Gremlin API cannot run SQL-like queries over raw JSON documents, and it does not provide document-level query constructs such as SELECT over nested JSON. It is the wrong choice when the primary requirement is simple, schema-free JSON document storage and retrieval.

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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.