Key advantages of Azure Stream Analytics

Let's quickly review how traditional streaming solutions are built; the core deployment starts with procuring and setting up the basic infrastructure necessary to host the streaming solution. Once this is done, we can then build the ingress and egress solution on top of the deployed infrastructure.

Once the core infrastructure is built, customer tools will be used to build business intelligence (BI) or machine-learning integration. After the system goes into production, scaling during runtime needs to be taken care of by capturing the telemetry and building and configuration of HW/SW resources as necessary. As business needs ramp up, so does the monitoring and troubleshooting.

The following screenshot illustrates how a traditional physical infrastructure based  streaming solutions are built:

Traditional infrastructure model to deploy Streaming services

As we can see in the illustration following configuration, building and managing real-time Analytics solutions is super-easy and cost-effective with Azure Stream Analytics, which provides a fully managed, resilient, and scalable platform that allows customers to focus on business logic and not worry about infrastructure setup and management. SQL-like query language drastically reduces the learning curve and development cost for the developers: 

Azure Streaming Analytics is a PaaS solution and doesn't need any physical infrastructure components