TLDR: KQL (Kusto Query Language), introduced in 2017, is a powerful and highly efficient query language optimized for working with large datasets in Azure Data Explorer and other Microsoft services like Azure Monitor and Log Analytics. It is designed for querying structured, semi-structured, and unstructured data with a focus on log and telemetry analysis.

https://learn.microsoft.com/en-us/azure/data-explorer/kusto-query-language

KQL is built for simplicity and performance, using a declarative syntax that resembles SQL while focusing on analytical operations. It enables users to filter, sort, and summarize massive datasets with minimal code. Features like pipe operators and inline summarization allow seamless chaining of commands to perform complex queries efficiently.

https://learn.microsoft.com/en-us/azure/data-explorer/kusto/query

One of the strengths of KQL is its integration with time-series data. It includes built-in functions for time-based analysis, anomaly detection, and visualization, making it ideal for scenarios like monitoring application performance and detecting trends in telemetry data. Its time-series capabilities are pivotal in platforms like Azure Monitor and Azure Sentinel.

https://learn.microsoft.com/en-us/azure/data-explorer/time-series

KQL also supports advanced operations like joins, unions, and data transformations, enabling users to perform relational and non-relational queries within the same framework. It includes operators like `extend`, `project`, and `summarize`, which provide flexibility for data manipulation and transformation. This makes it a versatile choice for querying diverse datasets.

https://learn.microsoft.com/en-us/azure/data-explorer/kusto/query/operators

Security and optimization are integral to KQL, with features like row-level security, column-level security, and query execution plans. It provides granular control over access to data and helps users optimize query performance by identifying inefficiencies in their scripts, ensuring high reliability and scalability in enterprise environments.

https://learn.microsoft.com/en-us/azure/data-explorer/kusto/query/best-practices