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Data integrations overview

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Data ingestion is the process used to load data from one or more sources into Azure Data Explorer. Once ingested, the data becomes available for query. Azure Data Explorer provides several connectors for data ingestion.

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

Overview

Query integrations

Visualization integrations

The following tables summarizes the available data connectors, tools, and integrations.

Name Functionality Supports streaming? Supports free cluster? Type Use cases
Apache Kafka Ingestion ✔️ First party, Open source Logs, Telemetry, Time series
Apache Flink Ingestion ✔️ Open source Telemetry
Apache Log4J 2 Ingestion ✔️ ✔️ First party, Open source Logs
Apache Spark Export

Ingestion		 Open source Telemetry
Apache Spark for Azure Synapse Analytics Export

Ingestion		 First party Telemetry
Azure Cosmos DB Ingestion ✔️ First party Change feed
Azure Data Factory Export

Ingestion		 First party Data orchestration
Azure Event Grid Ingestion ✔️ First party Event processing
Azure Event Hubs Ingestion ✔️ First party Messaging
Azure Functions Export

Ingestion		 First party Workflow integrations
Azure IoT Hubs Ingestion ✔️ First party IoT data
Azure Stream Analytics Ingestion ✔️ First party Event processing
Fluent Bit Ingestion Open source Logs, Metrics, Traces
Logstash Ingestion Open source Logs
NLog Ingestion ✔️ ✔️ First party, Open source Telemetry, Logs, Metrics
Open Telemetry Ingestion ✔️ Open source Traces, Metrics, Logs
Power Automate Export

Ingestion		 First party Data orchestration
Serilog Ingestion ✔️ ✔️ First party, Open source Logs
Splunk Ingestion Open source Logs
Splunk Universal Forwarder Ingestion Open source Logs
Telegraf Ingestion ✔️ Open source Metrics, Logs

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

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