In the latest release of SQL Servers (SQL Server 2019), Microsoft added a range of tools and services that enhanced its compatibility with Azure. We’ll take a closer look at the connection between SQL Server 2019 and Azure as we can’t deny the importance of these two immense services in DBMS.
Since Microsoft Azure SQL is a cloud-based service that was designed along the lines of SQL Server, it, therefore, shares similar features with on-premises SQL Server. We’ll discuss how these two database systems connect with each other.
In SQL Server 2019, Microsoft is bringing Azure SQL Database Managed Instance to general availability (GA).
What Is Azure and SQL Server?
Microsoft Azure SQL Database is an intelligent and fully managed relational cloud database service that provides the broadest SQL Server engine compatibility for users. Microsoft Azure is a cloud computing service that allows for the building, testing, deployment, and management of a wide variety of applications and services using a wide network of Microsoft-managed data centers.
Azure (formerly known as Windows Azure) supports different programming languages, frameworks, and tools, including Microsoft-specific and third-party systems and software while providing platform as a service (PaaS), software as a service (SaaS), and infrastructure as a service (IaaS).
On the other hand, Microsoft SQL Server is a relational database management system that supports a wide range of transaction processing, analytics applications, and business intelligence. Microsoft releases different versions of SQL Server with the latest being SQL Server 2019.
Since Azure SQL is based on SQL Server, they share some similarities in both compatibility and functionality as outlined below:
Deployment of Big Data Clusters
With its support for the Linux operating system, it is possible to integrate SQL Server 2019 with Spark, the HDFS, and other big data components. The big data clusters of SQL Server 2019 can be easily deployed in any cloud with a managed Kubernetes service because it ensures a predictable, fast, and elastically scalable deployment. An example of such service is the Azure Kubernetes Service (AKS), or in on-premises Kubernetes clusters, like AKS on Azure Stack.
In terms of programming, Azure SQL is built so that SQL developers can easily use it for communication and authentication. You just have to change the value of a parameter in the connection string to access Azure SQL.
Besides XML indexing and typed XML, SQL Azure supports all data types supported by SQL Server including specialized ones such as spatial data types.
Presence of Machine Learning Services
Both Microsoft Azure SQL Database and SQL Server 2019 support machines learning services. With this feature, users no longer need to move data out of the database to train and operationalize machine learning models.
Azure Data Studio
Azure Data Studio is one of the new products being introduced by Microsoft. However, the product itself isn’t particularly new, though because it was birthed after rebranding the SQL Operations Studio which is the cross-platform front-end tool for SQL Server. It can be used to connect to SQL Server both in the cloud and on-premises, edit and run queries; create custom dashboards; visualize data with the built-in charting of your result sets, and analyze data.
With the overhaul and rebranding, Microsoft intends making the Azure Data Studio more modular, to enable it to work with other data sources apart from SQL Server. The introduction of an add-in to the modular design will allow the product to easily work with SQL Server 2019.
SQL Database Managed Instance
With Managed Instances, you can actually migrate an large number of your SQL Server databases from your virtual machines (on-premises) to Azure SQL Database without affecting your apps.