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Query integrations overview

Kusto Query Language (KQL) is a powerful tool to explore your data and discover patterns, identify anomalies and outliers, create statistical modeling, and more. Use KQL to explore your data in different environments, and in other Microsoft services.

Use the following filters to see other connectors, tools, and integrations that are available for your use case.

The following tables summarize the available query connectors, tools, and integrations.

Name Functionality Roles Use cases
Apache Spark Query, Ingest, and Export Data Analyst, Data Scientist Machine learning (ML), Extract-Transform-Load (ETL), and Log Analytics scenarios using any Spark cluster
Apache Spark for Azure Synapse Analytics Query, Ingest, and Export Data Analyst, Data Scientist Machine learning (ML), Extract-Transform-Load (ETL), and Log Analytics scenarios using Synapse Analytics Spark cluster
Azure Functions Query, Ingest, and Orchestrate Data Engineer, Application Developer Integrate Azure Data Explorer into your serverless workflows to ingest data and run queries against your cluster
JDBC Query Application Developer Use JDBC to connect to Azure Data Explorer databases and execute queries
Logic Apps Query and Orchestrate Low Code Application Developer Run queries and commands automatically as part of a scheduled or triggered task.
Matlab Query Data Analyst, Data Scientist Analyse data, develop algorithms and create models.
ODBC Query Application Developer Establish a connection to Azure Data Explorer from any application that is equipped with support for the ODBC driver for SQL Serve.
Power Apps Query and Orchestrate Low Code Application Developer Build a low code, highly functional app to make use of data stored in Azure Data Explorer
Power Automate Query and Orchestrate Low Code Application Developer Orchestrate and schedule flows, send notifications, and alerts, as part of a scheduled or triggered task

For more information about connectors and tools, see Integrations overview.