Azure SQL Devs’ Corner

Azure SQL can read Azure Data Lake storage files using Synapse SQL external tables

Jovan Popovic December 10, 2020 Dec 10, 2020 12/10/20

Serverless Synapse SQL pool in Azure Synapse Analytics is a T-SQL query engine that enables you to read the files placed on Azure storage. You can easily integrate your Azure SQL engine with Synapse SQL to delegate big data analytics and analyze large amount of data placed on Azure.

Using an Azure Container Instance to convert a BAK to BACPAC for Import into Azure SQL Database

Davide Mauri December 9, 2020 Dec 9, 2020 12/9/20

Importing a SQL Server backup into an Azure SQL Database is not a trivial task. Here's how to automate the process of converting a .bak to .bacpac file using Docker Containers, Powershell and some automation.

Autoscaling with Azure SQL Hyperscale

Davide Mauri December 3, 2020 Dec 3, 2020 12/3/20

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 and...

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

Drew Skwiers-Koballa November 30, 2020 Nov 30, 2020 11/30/20

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.

Continuous Delivery for Azure SQL DB using Azure DevOps Multi-stage Pipelines

Arvind Shyamsundar October 28, 2020 Oct 28, 2020 10/28/20

Multi-stage pipelines in Azure DevOps offer a rich, declarative, YAML-based mechanism to implement and customize Continuous Delivery for Azure SQL.

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

Dimitri Furman October 20, 2020 Oct 20, 2020 10/20/20

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

Davide Mauri October 19, 2020 Oct 19, 2020 10/19/20

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, API, and...

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

Silvano Coriani October 12, 2020 Oct 12, 2020 10/12/20

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

Silvano Coriani October 12, 2020 Oct 12, 2020 10/12/20

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 ...

Build your full-PaaS IoT solution with Azure SQL Database

Silvano Coriani October 12, 2020 Oct 12, 2020 10/12/20

IoT with Azure SQL IoT solutions usually include several components that spans from device communication and management to event processing and data ingestion and analysis. Deploying all these components independently on compute, network and storage based infrastructures can be a complex and time consuming task, but nothing compared to manage...