Azure Stream Analytics (ASA) may be used for real-time insights from devices, sensors, infrastructure, and applications.
ASA is optimized to get streaming data from Azure Event Hubs and Azure Blob Storage. ASA SQL-like queries run continuously against the stream of incoming events. The results can be stored in Blob Storage, Event Hubs, Azure Tables and Azure SQL database. So if the output is stored in Event Hub it can become the input to another ASA job to chain together multiple real-time queries. `
Azure Stream Analytics supports processing events in three data formats: CSV, JSON, and Avro.
Stream Analytics ingests data from Azure Event Hubs (including Azure Event Hubs from Apache Kafka), Azure IoT Hub, or Azure Blob Storage. The query, which is based on SQL query language, can be used to easily filter, sort, aggregate, and join streaming data over a period. You can also extend this SQL language with JavaScript and C# user-defined functions (UDFs).
An Azure Stream Analytics job consists of an input, query, and an output. You can do the following tasks with the job output:
- Route data to storage systems like Azure Blob Storage, Azure SQL Database, Azure Data Lake Store, and Azure Cosmos DB.
- Send data to Power BI for real-time visualization.
- Store data in a Data Warehouse service like Azure Synapse Analytics to train a machine learning model based on historical data or perform batch analytics.
- Trigger custom downstream workflows by sending the data to services like Azure Functions, Azure Service Bus Topics, or Azure Queues.
ASA is typically used as one of components for real-time remote management and monitoring.
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