AZ-900 Describe Azure architecture and services Practice Question
Which Azure service provides a managed Apache Kafka-compatible event streaming service for high-throughput data pipelines?
⚠ Common exam trap
Candidates often confuse Azure Event Hubs with Azure Service Bus because both handle messages, but Event Hubs is optimized for high-throughput event ingestion and Kafka compatibility, while Service Bus is for enterprise messaging with features like sessions and dead-lettering.
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 Event Hubs
Azure Event Hubs is the correct answer because it provides a fully managed, native Apache Kafka-compatible event streaming platform designed for high-throughput data ingestion and processing. It supports the Kafka protocol (including Kafka Connect and Kafka Streams) without requiring you to run any Kafka clusters, making it ideal for real-time data pipelines and analytics.
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 Service Bus
Why it's wrong here
Azure Service Bus is a fully managed enterprise broker with queues and topics that provide advanced features such as sessions, transactions, duplicate detection, and scheduled messages. It excels at reliable, ordered, at-least-once delivery of business messages, but its throughput and latency profile are not built for high-volume streaming workloads. Because it lacks partitioning and a stream-style consumer model, it cannot match Event Hubs' ability to ingest and replay millions of data points per second.
- ✓
Azure Event Hubs
Why this is correct
Azure Event Hubs is the Azure-native, fully managed event streaming platform that is architecturally equivalent to Apache Kafka, supporting the Kafka protocol for compatibility. It ingests millions of events per second with partitioned throughput, consumer groups, and configurable retention that enables event replay and distributed processing. This makes it the correct choice for telemetry streams, real-time analytics, and event-driven ingestion at scale.
- ✗
Azure Queue Storage
Why it's wrong here
Azure Queue Storage is a simple, REST-based messaging store used to decouple app components for asynchronous processing, with per-message size capped at 64 KB. It offers no native topic fan-out, no partitioning, and only best-effort ordering, making it far too limited for Kafka-scale event streaming. While inexpensive and convenient for basic work queues, it is unsuitable for ingesting continuous telemetry or building real-time analytics pipelines.
- ✗
Azure Event Grid
Why it's wrong here
Azure Event Grid is a reactive event-routing backbone that delivers discrete events like resource state changes or custom application notifications to subscribers. Its architecture is optimized for low-latency pub/sub patterns with dead-lettering and retry, but it does not support the continuous, partitioned, replayable data streams characteristic of Kafka. Thus, while it can handle millions of events per second, it is not designed for sustained high-throughput telemetry ingestion or analytics pipelines.
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