KQL allows data to be queried as it’s ingested, and can quickly analyze structured, semi-structured, and unstructured data, including free text, using built-in operators and functions for trend analysis, pattern recognition, anomaly detection, forecasting, and machine learning capabilities.

The Kusto Query Language (KQL) provides a simple yet powerful syntax that allows anyone to query, analyze, and visualize data to get insights in real-time.

The end-to-end data flow diagram in Eventstream provides a comprehensive understanding of the data flow and organization.Ī KQL database is a fast, powerful, scalable, and highly available tool that is designed to handle large volumes of data. It also offers a drag and drop experience that enables you to create event data processing, transforming, and routing logic without requiring any coding experience. The Eventstream feature allows you to capture real-time events from a variety of sources such as Azure Event Hubs, custom applications, and even a sample dataset of taxi rides data and stock rates. In this blog post, we’ll learn about the integration between Eventstream and a KQL database, both of which are a part of the Real-Time Analytics experience. Synapse Real-Time Analytics in Microsoft Fabric can help you capture, transform, route, analyze and visualize huge amounts of real-time data from different sources in a matter of seconds.

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