KQL Editor

The KQL Editor is a web-based workspace for composing, validating, and executing Kusto Query Language (KQL) queries. It targets data engineers, data scientists, BI developers, and analysts who need rapid, in-browser access to Azure Data Explorer clusters or local sample data without desktop tools. It supports iterative development, debugging, and sharing reproducible results across teams, making prototyping, hypothesis testing, and KQL education more efficient. It emphasizes correctness, performance insight, and safe access controls when connecting to external data sources.
Conceptually, the tool accepts inputs such as cluster URL, database, and authentication method, then constructs and submits KQL statements to the configured data source. It returns results as a structured table with column metadata, plus execution time and data size. A query history enables reuse, while templates and snippets speed common patterns. It supports ad-hoc queries and more complex pipelines involving joins, unions, and time-based filters.
The processing pipeline performs syntax validation, semantic checks, and result formatting. It surfaces errors with location hints, offers light autocomplete from the current schema, and supports parameterized queries. Results render in a tabular view with optional pagination and can be exported to CSV or JSON. Developers can assess performance and cardinality in a focused browser environment.
Unique value lies in browser-based access to safe, read-only exploration, with export and template-driven workflows. Use cases include rapid prototyping for dashboards, KQL education, and sharing reproducible queries with teammates. It avoids local dependencies while enabling collaboration by exporting queries and results and by preserving a history of edits.