Quick Answer
The answer is Azure Event Hubs with Kafka protocol support. This service is the correct choice because it acts as a fully managed, high-throughput ingestion layer that natively speaks the Kafka wire protocol, allowing your on-premises Kafka cluster to stream data directly into Event Hubs without custom gateways or code, while handling 10,000 events per second with sub-second latency—well within the required 5-minute window. On the DP-203 exam, this scenario tests your understanding of how to bridge on-premises streaming sources to Azure Synapse using native protocol compatibility, and a common trap is selecting Azure Stream Analytics or IoT Hub, which add unnecessary complexity or lack Kafka protocol support. Remember the key phrase: “Kafka protocol support” on Event Hubs means you can ingest from on-premises Kafka to Azure Synapse without a separate connector—think of it as a direct pipeline where Kafka producers see Event Hubs as just another Kafka broker.
This DP-203 practice question tests your understanding of develop data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are designing a near-real-time data processing solution for a retail company. The source is a Kafka cluster on-premises. The target is an Azure Synapse Dedicated SQL Pool. The solution must handle up to 10,000 events per second with less than 5-minute latency. Which Azure service should you use to ingest the data?
Azure Event Hubs (with Kafka protocol support)
Event Hubs supports Kafka protocol and can ingest 10K events/sec with low latency.
Azure Data Lake Storage Gen2
Why wrong: ADLS Gen2 is a storage service, not an ingestion service.
Azure IoT Hub
Why wrong: IoT Hub is for IoT device telemetry, not Kafka streams.
Azure Stream Analytics
Why wrong: Stream Analytics is for processing, not direct ingestion from Kafka.
Answer choices
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 (with Kafka protocol support)
Azure Event Hubs with Kafka protocol support is the correct choice because it provides a fully managed, high-throughput data ingestion service that can handle up to 10,000 events per second with sub-second latency, and it natively supports the Kafka protocol, allowing direct integration with your on-premises Kafka cluster without custom code or additional gateways. This meets the near-real-time requirement (<5-minute latency) and scales to the specified throughput.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Azure Event Hubs (with Kafka protocol support)
Why this is correct
Event Hubs supports Kafka protocol and can ingest 10K events/sec with low latency.
Related concept
Read the scenario before looking for a memorised answer.
Azure Data Lake Storage Gen2
Why it's wrong here
ADLS Gen2 is a storage service, not an ingestion service.
Azure IoT Hub
Why it's wrong here
IoT Hub is for IoT device telemetry, not Kafka streams.
Azure Stream Analytics
Why it's wrong here
Stream Analytics is for processing, not direct ingestion from Kafka.
Common exam traps
The trap here is that candidates often confuse Azure Stream Analytics as an ingestion service, but it is a processing engine that requires an ingestion layer (like Event Hubs) first, and they may overlook that Azure Event Hubs natively supports the Kafka protocol, making it the direct replacement for Kafka ingestion in Azure.
Detailed technical explanation
Azure Event Hubs implements the Kafka protocol at the wire level (using the same binary protocol and API), enabling existing Kafka producers to publish events directly to Event Hubs without any code changes—just a connection string update. Under the hood, Event Hubs uses partitioned consumer groups and auto-inflate to dynamically scale throughput units (TUs) or processing units (PUs) to handle spikes up to 10,000 events per second, ensuring consistent low-latency ingestion. In a real-world scenario, if the Kafka cluster bursts beyond 10,000 events per second, Event Hubs can auto-scale to accommodate the load, whereas other services like IoT Hub would throttle or reject messages.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Event Hubs (with Kafka protocol support) — Azure Event Hubs with Kafka protocol support is the correct choice because it provides a fully managed, high-throughput data ingestion service that can handle up to 10,000 events per second with sub-second latency, and it natively supports the Kafka protocol, allowing direct integration with your on-premises Kafka cluster without custom code or additional gateways. This meets the near-real-time requirement (<5-minute latency) and scales to the specified throughput.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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