The correct answer is Azure Event Hubs.

Azure Event Hubs is a purpose built ingestion service for high volume streaming telemetry and logs and it scales with partitions and throughput units to handle large event rates with low latency. It provides durable capture to Blob or Data Lake for replay and batch analytics and it integrates directly with downstream real time processors such as Azure Stream Analytics, Azure Functions, and Azure Databricks so dashboards and alerts can be powered immediately.

Azure Event Hubs also supports consumer groups so multiple independent downstream consumers can read the same stream and it offers throughput controls and partitioning that are essential for predictable, high throughput log ingestion.

Azure Databricks is a data processing and analytics platform rather than an ingestion endpoint. Databricks commonly consumes streams from services like Azure Event Hubs to perform processing and analytics, so it is not the primary choice for ingesting high volume logs.

Azure IoT Hub is optimized for secure device to cloud messaging and device management. It is ideal for scenarios that require per device identity and bi directional communication, but it is not the general purpose, high throughput ingestion service for arbitrary application logs where Azure Event Hubs is preferred.

Azure Data Factory is focused on orchestration and batch ETL and it does not provide the same low latency, high throughput streaming ingestion capabilities required for real time dashboards and alerts. Data Factory is better suited for scheduled or batch data movement and transformation.

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