Azure SQL Devs’ Corner

Voices from the Azure SQL PM Team, focusing on development and developers

Autoscaling with Azure SQL Hyperscale

Azure SQL Hyperscale is the latest architectural evolution of Azure SQL, which has been natively designed to take advantage of the cloud. One of the main key features of this new architecture is the complete separation of Compute Nodes and Storage Nodes. This allows for the independent scale of each service, making Hyperscale more flexible...

Seasons of Serverless Challenge 1: Azure Functions and Azure SQL Database serverless

Throughout the next seven weeks we'll be sharing a solution to the week's Seasons of Serverless challenge that integrates Azure SQL Database serverless with Azure serverless compute. Learn how to develop an Azure Function that leverages Azure SQL database serverless with Challenge 1 of the Seasons of Serverless challenge.

Testing performance of Azure SQL Database as a key-value store

Executive summary Our testing shows that Azure SQL Database can be used as a highly scalable low latency key-value store. Starting with a cost-efficient 4-core General Purpose database, we see an order of magnitude increase in workload throughput as we increase dataset size by 100x and scale across the spectrum of database SKUs to a Business ...

Serverless Streaming At Scale with Azure SQL

(image) Just before Ignite, a very interesting case study done with RXR has been released, where they showcased their IoT solution to bring safety in buildings during COVID times. It uses Azure SQL to store warm data, allowing it to be served and consumed to all downstream users, from analytical applications to mobile clients, dashboards, ...

Optimize storage usage for large volumes of IoT data with Azure SQL

IoT with Azure SQL IoT solutions are generally producing large data volumes, from device to cloud messages in telemetry scenarios to device twins or commands that need to be persisted and retrieved from users and applications. Whether we need to store data in “raw” formats (like JSON messages emitted by different devices), to preserve and...

Ingest millions of events per second on Azure SQL leveraging Shock Absorber pattern

IoT with Azure SQL IoT workloads can be characterized by high rates of input data, on both steady and burst streams, to be ingested from devices. A common design pattern for relational database systems involves a “landing zone” (or staging area) which is optimized for “absorbing the shock” of this high and spikey input rate, before ...