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Describe Azure architecture and servicesmediumMultiple ChoiceObjective-mapped

AZ-900 Describe Azure architecture and services Practice Question

Which Azure service provides an enterprise-grade, fully managed graph database as a service?

⚠ Common exam trap

It's easy for candidates to confuse Azure Cosmos DB's multiple APIs (e.g., SQL, MongoDB, Cassandra, Table, Gremlin) and incorrectly assume that Azure SQL Database or Azure Table Storage can handle graph workloads, when only the Gremlin API within Cosmos DB is purpose-built for graph databases.

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 for Gremlin

Azure Cosmos DB for Gremlin is the correct answer because it provides a fully managed, enterprise-grade graph database service that uses the Apache TinkerPop Gremlin graph traversal language. It supports graph data models with vertices and edges, enabling complex relationship queries at global scale with turnkey distribution and SLA-backed performance.

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 SQL Database

    Why it's wrong here

    Azure SQL Database is a fully managed relational database service based on the SQL Server engine. It organizes data into tables with defined schemas and uses foreign keys to relate rows, which is not the same as a graph database where relationships are first-class entities stored as edges. Graph queries that traverse multiple relationship hops are inefficient or verbose to express in SQL compared to Gremlin.

  • Azure Cosmos DB for Gremlin

    Why this is correct

    Azure Cosmos DB for Gremlin is a fully managed graph database service that implements the Apache TinkerPop Gremlin traversal language on top of Cosmos DB. It stores entities as vertices and relationships as edges, enabling efficient traversal queries for highly connected data. With features like global distribution, multi-language SDKs, and flexible schemas, it is the correct choice among these options for graph workloads.

  • Azure Table Storage

    Why it's wrong here

    Azure Table Storage is a NoSQL key-value store that holds large amounts of structured data as entities with partition and row keys. It does not represent relationships between entities, and there is no graph query engine to perform edge traversals or pattern matching across connected data. It is designed for fast, cost-effective storage of tabular data, not for graph use cases.

  • Azure Cache for Redis

    Why it's wrong here

    Azure Cache for Redis is an in-memory data store built on the open-source Redis engine, commonly used for caching, real-time analytics, and session state management. While it supports rich data structures like sets, hashes, and sorted sets, it lacks a graph model and does not provide a query language for traversing relationships between connected entities. Its purpose is low-latency access to frequently used data, not graph processing.

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