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A company is building an IoT solution where millions of devices will send small data packets (telemetry) frequently. The data needs to be ingested into Azure for real-time processing and long-term storage in Data Lake. The solution must handle massive scale, allow multiple consumer groups to read the same data stream independently, and provide retention for historical analysis. Which Azure service should be used for the data ingestion layer?
- AAzure IoT Hub
- BAzure Stream Analytics
- CAzure Service Bus Queues
- DAzure Event Hubs
Show answer & explanationAnswer & explanation
Correct answer: D. Azure Event Hubs
Azure Event Hubs is a highly scalable data streaming platform and event ingestion service designed for high-throughput scenarios involving millions of events per second. It supports multiple consumer groups, allowing independent processing of the same data stream, and provides data retention, making it ideal for ingesting IoT telemetry for real-time and historical analysis.
Why the other options are wrong
- A. Azure IoT Hub is for device management and bidirectional communication with IoT devices, but Event Hubs is specifically for the high-volume data ingestion aspect of the telemetry stream itself.
- B. Azure Stream Analytics is a real-time analytics engine, it consumes data but is not the primary ingestion service for raw telemetry from devices.
- C. Azure Service Bus Queues are for reliable message delivery between applications, not for high-throughput, multi-consumer stream ingestion from millions of devices.
Event Hubs for Big Data Ingestion
Azure Event Hubs acts as a front door for ingesting massive amounts of data from diverse sources, especially in big data and IoT scenarios.
- Handles millions of events per second.
- Supports multiple consumer groups for parallel processing.
- Provides configurable data retention for historical analysis.
Memory trick: IoT data flows through Event Hubs, the super-stream collector.