MATCH_RECOGNIZE in Azure Stream Analytics significantly reduces the complexity and cost associated with building, modifying, and maintaining queries that match sequence of events for alerts or further data computation.
What is Azure Stream Analytics?
Azure Stream Analytics is a fully managed serverless PaaS offering on Azure that enables customers to analyze and process fast moving streams of data and deliver real-time insights for mission critical scenarios. Developers can use a simple SQL language, extensible to include custom code, in order to author and deploy powerful analytics processing logic that can scale-up and scale-out to deliver insights with milli-second latencies.
Traditional way to incorporate pattern matching in stream processing
Many customers use Azure Stream Analytics to continuously monitor massive amounts of data, detecting sequence of events and deriving alerts or aggregating data from those events. This in essence is pattern matching.
For pattern matching, customers traditionally relied on multiple joins, each one detecting a single event in particular. These joins are combined to find a sequence of events, compute results or create alerts. Developing queries for pattern matching is a complex process and very error prone, difficult to maintain and debug. Also, there are limitations when trying to express more complex
Azure Stream Analytics is a fully managed PaaS offering that enables real-time analytics and complex event processing on fast moving data streams. Thanks to zero-code integration with over 15 Azure services, developers and data engineers can easily build complex pipelines for hot-path analytics within a few minutes. Today, at Inspire, we are announcing various new innovations in Stream Analytics that help further reduce time to value for solutions that are powered by real-time insights. These are as follows:
Bringing the power of real-time insights to Azure Event Hubs customers
Today, we are announcing one-click integration with Event Hubs. Available as a public preview feature, this allows an Event Hubs customer to visualize incoming data and start to write a Stream Analytics query with one click from the Event Hub portal. Once the query is ready, they will be able to operationalize it in few clicks and start deriving real time insights. This will significantly reduce the time and cost to develop real-time analytics solutions.
One-click integration between Event Hubs and Azure Stream Analytics
Augmenting streaming data with SQL reference data support
Reference data is a static or slow changing dataset used to augment real-time data streams to deliver more