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 company has an existing IoT application that uses Apache Cassandra for time-series sensor data. They want to migrate to Azure's fully managed NoSQL database service while continuing to use the Cassandra Query Language (CQL) and benefiting from global distribution and low latency. Which Azure Cosmos DB API should they use?
⚠ Common exam trap
It's easy for candidates to confuse the 'Cassandra API' with the 'Core (SQL) API' because both support SQL-like syntax, but only the Cassandra API uses the native CQL wire protocol and wide-column storage model required for time-series sensor data.
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
✓
Cassandra API
The Cassandra API for Azure Cosmos DB is wire-protocol-compatible with Apache Cassandra, meaning you can use existing CQL (Cassandra Query Language) tools, drivers, and code with minimal changes. It provides a fully managed, globally distributed NoSQL database with low-latency reads and writes, which directly matches the company's requirement to migrate from self-managed Cassandra while preserving their CQL-based application logic.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Core (SQL) API
Why it's wrong here
The Core (SQL) API in Azure Cosmos DB uses a SQL-like query syntax and a schema-agnostic JSON document model. It does not implement the Cassandra Query Language (CQL) or the Apache Cassandra wire protocol, so an existing Cassandra application's client drivers and queries would not work. Migrating to this API would require rewriting all query logic and reshaping the time-series data model, making it a poor fit for a Cassandra-based workload.
- ✗
MongoDB API
Why it's wrong here
The MongoDB API is built for workloads that use MongoDB's document model and its own query language, not for Cassandra clients. It communicates via the MongoDB wire protocol instead of CQL, and stores data as BSON documents, so an existing Cassandra time-series application would need to be completely reengineered. Even the data modeling approach differs: Cassandra uses partition keys and clustering columns for ordered time-series, whereas MongoDB uses collections and flexible schemas, so this API is not compatible.
- ✓
Cassandra API
Why this is correct
The Cassandra API provides a native compatibility layer for the Apache Cassandra wire protocol and CQL, allowing existing Cassandra drivers, queries, and schemas to work with minimal changes. This makes it the only option that supports a seamless migration from an on-premises Cassandra cluster to Azure Cosmos DB while preserving the time-series data model and query patterns. Cosmos DB then adds global distribution, multi-region writes, and a fully managed SLA on top of that Cassandra compatibility.
- ✗
Gremlin API
Why it's wrong here
The Gremlin API is designed for graph data and uses the Gremlin traversal language to query vertices and edges, which has no concept of time-series tables or CQL. A typical IoT workload that relies on Cassandra's clustering columns for timestamp-ordered data cannot be expressed as a graph without a major redesign. The Gremlin API would also require new client drivers and completely different query syntax, making it unsuitable for this Cassandra-based application.
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Azure Cosmos DB
Azure Cosmos DB is a fully managed, globally distributed NoSQL database service that offers fast reads and writes anywhere in the world with automatic scaling and multiple consistency models.
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