Sending and consuming events in Avro format

Azure Stream Analytics currently supports three formats for input event serialization: Avro, CSV and JSON. This blog post will demonstrate how to send events to an input source in the Avro format, to be later consumed by a Stream Analytics jobFor examples below, assume that we are sending events to an Event Hub instance.  …


(Cross Post) Azure Stream Analytics and DocumentDB for your IoT application

Support for output to Azure DocumentDB from Stream Analytics jobs has been highly requested by customers and was the top-voted idea on the Azure Feedback Forum.  Stream Analytics and DocumentDB are both core services in the Azure IoT Suite and have recently been updated to include first-class integration with one another.  Today the integration between these two services…


Query Pattern of the Week: Use expressions inside a TIMESTAMP BY clause

Azure Stream Analytics allows expressing complex event processing rules using a simple SQL-like query language. Given the temporal nature of Stream Analytics queries, it is important to specify a timestamp for every input event.  By default, Stream Analytics will use arrival time of the input event – e.g. if Event Hub is used as an…


Stream Analytics updates for the Azure IoT Suite

Today Microsoft announced the availability of the Azure IoT Suite, a collection of preconfigured solutions that enable you to easily develop, deploy, and scale your Internet of Things solutions. Stream Analytics is a core service in the IoT Suite and as part of this announcement, we have delivered several new features today.  Included in today’s…


Query Pattern of the Week: Send data to multiple outputs

Have you checked out our team’s collection of Common Stream Analytics Query Patterns? This location acts as a repository for query patterns commonly used by our customers. One pattern that frequently comes up in real-world applications is directing job data to multiple outputs to enable both a hot path and a cold path for data….


Azure Stream Analytics @ The First Ever Cortana Analytics Workshop!

The Azure Stream Analytics (ASA) team was proud to be a part of the first ever Cortana Analytics Workshop that was held September 10-11, 2015. The 2-day event was sold out, we had around 700 attendees, around 500 customers/partners from 293 companies and 35 countries (almost 1 in 5 attendees were non-US). For those newly…


New: Support for Power BI Groups and Documentation Updates

As the fall begins to kick into high gear, we are excited to have another great new feature to share with you today: Support for pushing output from your Stream Analytics job to Power BI Groups, allowing the output and any associated dashboards etc. to be shared with other Power BI users. Groups in Power…

(Cross Post) Refreshing reference data with Azure Data Factory for Azure Stream Analytics Jobs

Since we introduced the refresh capability of our Reference Data, we had been seeing a lot of asks on how the reference data could be created on a particular schedule. Some customers have used SSIS on a stand alone machine while others have written custom applications running on an Azure Virtual Machine which populates the reference data on a specific schedule….


Query Pattern of the Week: Specify logic for different cases

Last week we kicked off a new blog series to highlight a query pattern with a real world example every week.  This week we examine how to use CASE statements to specify conditional logic.  For more query patterns, check out the Common Stream Analytics Query Patterns page. Description: Evaluate one of multiple results based on…


Working with complex data types in Azure Stream Analytics

Azure Stream Analytics supports processing events in a variety of data formats (CSV, JSON, Avro). JSON and Avro can contain complex types such as nested objects (records) or arrays. Many Stream Analytics customers use nested data and we have received various questions related to processing events containing records and/or arrays. This blog post provides an…