Ingest real time streaming data in SQL Database tables

Ingest real time streaming data in SQL Database tables directly from the Azure SQL Portal

Do you have real time streaming data in Event Hub or IoT Hub?

Do you want to ingest that data in your without leaving your SQL Database?

Good news! You can now stream data into your SQL Database in a few simple clicks to enable a wide variety of scenarios such as connected car, remote monitoring, fraud detection and many more.

Data Engineers work with streaming data in SQL Database daily. However, ingesting streaming data in a SQL DB table has been fraught with complexity. Users have found it difficult to easily ingest, process and view real-time data without switching back and forth between services. This context switching makes it easy to lose track of one's place and setting up/configuration is prone to error.

Today, we are happy to announce real time streaming data into a SQL Database table directly from the Portal. Using Azure Stream Analytics, you can now ingest, process, view and analyze real time streaming data into a SQL Database table directly in the Portal, without switching context between services!


Key benefits

  • Minimum context switching: You can start from a SQL Database in the portal and start ingesting real-time data into a table without switching to any other service.
  • Reduced number of steps: The context of your database and table is used to pre-configure a Stream Analytics job.
  • Additional ease of use with preview data: Preview incoming data from the events source (Event Hub/IoT Hub) in the context of selected table

Get started today

Here are the 5 easy steps you can take within SQL Database to get started:

  1. In SQL Database portal, select the database where you want to ingest streaming data
  2. Select real time streaming events source (Event Hub/IoT Hub)
  3. Select/Create SQL table where you want to store your transformed events
  4. View incoming events and write/test SAQL query to transform events
  5. Start the stream analytics job which will start ingesting data from Step 2 to step 3

To get started, see the detailed documentation here.

Feedback and engagement

Engage with us and get early glimpses of new features by following us on Twitter at @AzureStreaming.

The Azure Stream Analytics team is highly committed to listening to your feedback and letting the user's voice influence our future investments. We welcome you to join the conversation and make your voice heard via our UserVoice page.


This article was originally published by Microsoft's ITOps Talk Blog. You can find the original article here.