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The Real-Time hub is used to discover and manage your streaming data in Fabric. Ingesting streaming data with the Real-Time hub is the first step in seamlessly integrating your data in Fabric, which, in turn, empowers analysts to extract real-time insights from the data. The rich set of available connectors ensures that regardless of your streaming source, you can effortlessly import data into Fabric.
This user flow shows how a data engineer can load and transform events from a wide variety of streaming sources into the Real-Time hub.
Steps
Browse to the Real-Time hub and select Get Events.
The supported connectors are shown. Choose a connector based on where your streaming source is located.
Provide connections to the source, including credentials.
Name the stream. A new eventstream is created and data starts to flow in.
For detailed information and steps, see Get events from supported sources.
Open the newly created eventstream.
Define data processing operations that transform the streaming data.
Add a destination to the stream.
For detailed information and steps, see Transformation operations and Add and manage destination.
Supported connectors
Microsoft sources
| Source | Description | Learn More |
|---|---|---|
| Azure Event Hubs | A fully managed real-time data ingestion service. | Learn more |
| Azure Service Bus (preview) | A messaging service for reliable communication. | Learn more |
| Azure IoT Hub | A platform for managing IoT devices and data. | Learn more |
| Azure SQL Database CDC | Capture and stream database changes in real time. | Learn more |
| Azure Database for PostgreSQL CDC | Stream changes from PostgreSQL databases. | Learn more |
| Azure Database for MySQL CDC | Stream changes from MySQL databases. | Learn more |
| Azure Cosmos DB CDC | Stream changes from Cosmos DB. | Learn more |
| Azure SQL Managed Instance CDC | Capture changes from SQL Managed Instances. | Learn more |
| SQL Server on VM DB CDC | Stream changes from SQL Server on VMs. | Learn more |
| Azure Data Explorer | Analyze large volumes of data in real time. | Learn more |
External sources
| External Source | Description | Learn More |
|---|---|---|
| Google Cloud Pub/Sub | A messaging service for real-time event streaming. | Learn more |
| Amazon Kinesis Data Streams | A platform for real-time data processing. | Learn more |
| Confluent Cloud Kafka | A cloud-native Kafka service for event streaming. | Learn more |
| Apache Kafka (preview) | A distributed event streaming platform. | Learn more |
| Amazon Managed Streaming for Apache Kafka | A managed Kafka service for streaming. | Learn more |
| MQTT | A lightweight messaging protocol for IoT. | Learn more |
| Solace PubSub+ | An advanced event broker for real-time messaging. | Learn more |
| Real-time weather | A source for real-time weather data. | Learn more |
Discrete events
| Event Source | Description |
|---|---|
| Azure Blob Storage events | Learn how to capture and process events from Azure Blob Storage. |
| Fabric Workspace Item events | Understand how to work with events from Fabric Workspace Items. |
| Fabric OneLake events | Explore event handling for Fabric OneLake. |
| Fabric Job events | Manage and process Fabric Job events effectively. |
Potential use cases
Your streaming data source is in a Confluent Kafka cluster, and you want to bring it to Fabric. The 'GetEvents' experience in Real-Time hub enables you to easily ingest data from your Confluent Kafka cluster into Fabric.