Azure SQL Devs’ Corner

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

Developing in the cloud with SQL Server Big Data Clusters: Getting Started
Developing in the cloud with SQL Server Big Data Clusters: Getting Started
When it comes to innovation, we realized that the world’s most valuable resource is no longer oil, but data. One of the biggest challenges we’re having today is how to integrate disparate data sources from many different places. If you're looking into how to work on Big Data Analytics solutions in Kubernetes, that's where Big Data Clusters...
Querying and visualizing data using SQLPad
Querying and visualizing data using SQLPad
SQLPad is an amazing free, open source, tool to run SQL Queries against a broad spectrum of popular databases, without the need to install and run something on-premises. It's lightweight, simple and just perfect if you need a no-frills tool to query and visualize data, to do some data exploration.
Microsoft.Data.SqlClient 2.0.0 is now available
Microsoft.Data.SqlClient 2.0.0 is now available
Microsoft.Data.SqlClient version 2.0.0 has been released, with several interesting features. Make sure you check it out if you are a .NET developer and you are using Azure SQL or SQL Server in your solutions. Microsoft.Data.SqlClient is the new, open source, official data access library that replaces System.Data.SqlClient
Go Azure SQL!
Go Azure SQL!
Go is a very popular programming language for developing microservices, Web APIs and other server-side applications, and Azure SQL can definitely be an option where to persist data for these applications in a scalable, reliable and modern way leveraging Microsoft SQL Server Driver for Go and ORM packages like Gorm. Give it a try!
JSON in your Azure SQL Database? Let’s benchmark some options!
JSON in your Azure SQL Database? Let’s benchmark some options!
Introduction Storing and retrieving data from JSON fragments is a common need in many application scenarios, like IoT solutions or microservice-based architectures. You can persist these fragments can be in a variety of data stores, from blob or file shares, to relational and non-relational databases, and there’s a long standing debate in...
Optimize Azure SQL Upsert scenarios
Optimize Azure SQL Upsert scenarios
Customers often need to move a dataset from a source system into a new destination, inserting rows that doesn't exist in a target table and update those that already exists. With this technique, we've been able to reduce the time needed to upsert a dataset of 2M rows against a target table with 30M rows from 20 hours to 20 minutes.