Azure Stream Analytics introduction

In the previous chapter, we discussed Azure Event Hub, which is a solution for receiving and processing thousands of messages per second, by introducing the implementation of event processor hosts. While it is great for workloads such as big data pipelines or IoT scenarios, it is not a solution to everything, especially if you want to avoid hosting VMs. Scaling such architectures can be cumbersome and nonintuitive; this is why there is Azure Stream Analytics, which is an event-processing engine designed for high volumes of data. It fills a gap where other services such as Event Hub or IoT Hub do not perform well (or where to do so they require much more skill and/or more sophisticated architecture), particularly for real-time analytics, anomaly detection, and geospatial analytics. It is an advanced tool for advanced tasks, which will greatly...