Azure SQL Database is a Relational Database service that is always up to date and designed for modern Cloud applications. It is part of the Azure SQL family. Most Database Management functions, such as upgrading, patching, backups, and monitoring, can be performed without the intervention of a person.

Azure SQL is a Cloud-based service modeled like SQL Server, allowing you to seamlessly migrate applications while maintaining familiar tools, languages, and resources.

In this article, you will learn how to connect Azure SQL to SQL Server Migration in detailed steps.

How does Migration work?

Azure SQL is a Cloud-based service developed along the lines of SQL Server, so you can easily move applications and keep using the tools, languages, and resources you’re familiar with. 

You can migrate SQL Server databases that are run on:

  • SQL Server on-premises.
  • SQL Server on Azure Virtual Machines.
  • Amazon Web Services (AWS) Elastic Compute Cloud (EC2).
  • AWS Relational Database Service (RDS).
  • Compute Engine in Google Cloud Platform (GCP).
  • Cloud SQL for SQL Server in GCP.

Azure provides three options to implement SQL Server in Azure:

  • IaaS on Azure—install and operate the database on Azure virtual machines (VMs).
  • PaaS on Azure—relocate your on-prem database to Azure SQL Database.
  • IaaS and PaaS—employ Azure SQL Database managed instances to gain both IaaS and PaaS traits.

Azure delivers free, automated tools that can help you migrate your on-premises SQL Server databases to Azure, regardless of your selected deployment model.

Azure SQL to SQL Server Migration: Options and Tools

There are several ways to connect to an Azure SQL database. Below is a list of IDEs that have the functionality to connect to the Azure SQL database

  • SQL server management studio
  • Visual Studio
  • Azure data studio
  • Azure portal
  • through PowerShell
  • using IP address

SQL Server Migration Tools

Let’s review the tools to help you migrate SQL Server to Azure.

1) Azure Migrate

This service is a unified migration platform that plays the role of a centralized hub capable of evaluating and migrating On-premises Servers, Infrastructure, Applications, and Data to Azure. It can be found within the Azure portal when searching for Azure Migrate.

This tool can be beneficial if you have any on-premises servers. It will enable you to complete the discovery of your data center and check dependencies between servers and applications.

Azure Migrate can spot any type of migration blockers during the evaluation phase,  offers recommendations for Azure SQL deployments, and provides monthly cost estimates and recommendations for target sizing.

For the actual migration step, you could use the tools for server migration or database migration. The tool is easy to use as the required instruments can be added from the hub based on your needs.

2) Data Migration Assistant

The Data Migration Assistant (DMA) is a desktop tool to help you complete single-database SQL Server migrations to Azure SQL Database.

This tool suggests performance and reliability revisions for your target environment. It enables you to migrate your schema, data, and uncontained objects from your source server to your target server.

DMA catches compatibility issues affecting database functionality and logically moves data between objects in your target and source databases.

The Data Migration Assistant can be installed on an on-prem server or a local machine with connectivity to the source databases. The latest version of the tool can be downloaded from the Microsoft Download Center. 

3) Azure Database Migration Service (DMS)

The Azure Database Migration Service supplies fully managed assistance to migrate on-premises databases or data warehouses to the managed Azure SQL Database platform. DMS allows you to migrate data, objects, and schema efficiently.

It conducts a pre-migration assessment to spot any issues that may preclude migration. It also enables you to pinpoint those features that may be unsupported or negatively affected.

When utilizing DMS, you must select a preferred Azure virtual network for provisioning. This is essential to guarantee connectivity to the source SQL Server databases.

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Azure SQL to SQL Server Migration Database

Here are the steps you’ll need to make to move your Azure SQL to SQL Server Migration:

Method 1: Azure SQL to SQL Server Migration using Data Migration Assistant


Below are the prerequisites needed to complete the Azure SQL to SQL Server Migration:

  • Download and install SQL Server the 2016 version or a later one.
  • Ensure that the TCP/IP protocol has been enabled, as this feature is disabled by default during SQL Server Express installation.
  • Restore the database to the SQL Server instance.
  • Create a database in Azure SQL Database.
  • A Microsoft Azure Virtual Network for Azure Database Migration Service has been created using the Azure Resource Manager deployment model. It offers site-to-site connectivity to your on-premises source servers through ExpressRoute or VPN.

Step 1: Pre-Migration

Ensure that the database can support the source environment. During the pre-migration stage, you should also assess migration feasibility, uncover resources, and determine and remediate potential impediments to migration.

Step 2: Discovery

The next step in the migration process is the discovery phase. During this phase, you will have to scan your network for all SQL Server instances and other appropriate features.

The Azure Migrate can be used to evaluate the migration suitability of each on-premises server and calculate their running expenses in Azure.

Step 3: Assessment

Reckon the compatibility of your on-premises SQL Server databases with Azure SQL Database. Starting with version 4.1, the Data Migration Assistant can supply suggestions for Azure target and the SKU that can sustain your workloads.

Here are the steps to perform the assessment:

  • Step A: Open the Data Migration Assistant (DMA)
  • Step B: Select File
  • Step C: In the Data Migration Assistant, click the New (+) icon, and choose the Assessment project type.
  • Step D: Set the name of your project; under Source, select SQL Server, and under Target, pick Azure SQL Database.
  • Step E: Choose the target server SQL Server version. This is the SQL Server version that you’ll be evaluating.

During an assessment, you have the possibility of choosing one or both of the following assessment report types:

  • Check database compatibility
  • Check feature parity

Both report types are selected by default.

  • Step F: Determine the source server instances, and provide the connection credentials.
  • Step G: Start Assessment; once the assessment is concluded, you can access the results under the Review results tab.
  • Step H: Determine which compatibility issues you will fix.
Azure SQL to SQL Server: Step 3a
Image Source

The reports generated by the assessment can also be exported to a shareable file, such as CSV. The exported file can be viewed in Excel, or other tools, to acquire specific details on issues and recommendations.

Once the assessment is done, the results will be displayed as shown in the below image:

Azure SQL to SQL Server Results

Step 4: Azure SQL to SQL Server Migration

Once the pre-migration stage is finalized, you can begin moving your data by employing the chosen migration strategy with Data Migration Assistant.

Here are the steps to be followed for Azure SQL to SQL Server Migration Database:

  • Step A: Open a new project and under Type, choose the Migration option
  • Step B: Specify a project name. Determine the source and target as SQL Server and Azure SQL Database, respectively.
  • Step C: Next, select the schema and data as the scope of migration and click on the Create button.
  • Step D: In the Data Migration Assistant, specify the source connection details for your SQL Server (e.g., server name, credentials) as well as the details of the target server (e.g., the source server name, target database, and credentials)
  • Step E: Establish and deploy schema objects to the target database.
  • Step F: Choose Start data migration and start observing the migration progress.

Step 5: Post-Migration

After completing the migration stage, you have the option of conducting post-migration tasks to ensure that things are working adequately.

Step 6: Remediation of applications

Once the data has been moved to your target environment, check if the apps that used to be connected to your original database can relate to and utilize the target database. Occasionally you might need to make changes to your applications.

Step 7: Testing

Conduct tests to validate your source and target database and to evaluate their performance. This can be done by setting up a set of validation queries. Put together a testing environment (an isolated copy of the databases that need to be tested), run both validation and performance tests, and examine the results.

Method 2: Azure SQL to SQL Server Migration using Hevo

PostgreSQL Dump Import

Hevo Data, a No-code Data Pipeline, helps you directly transfer data from Data Warehouses and Databases like Azure SQL and 150+ other data sources, Data Warehouses, or a destination of your choice such as SQL Server in a completely hassle-free & automated manner.

Hevo is fully managed and completely automates the process of loading data from your desired source, enriching it, and transforming it into an analysis-ready form without having to write a single line of code.

It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It supports moving data from Azure SQL DB to SQL Server & SQL Server to Azure hence you get a comprehensive solution.

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Frequently Asked Questions (FAQs)

Is Azure SQL Database the same as SQL Server?

In an SQL server, the only entity on the database server is the databases. Whereas in SQL Azure, databases from different customers can be hosted by a single database. Thus, Azure SQL is multitenant and shares its physical resources with all the clients who use the service.

Is Azure SQL compatible with SQL Server?

Any edition of SQL Server running on Azure is fully supported for IaaS(Infrastructure as a Service – Virtual Machine). You will achieve complete compatibility with legacy on-premises SQL deployments when combined with “Always On” availability groups. Customers must change their initiative’s compatibility level for existing Azure SQL databases because Microsoft does not do it automatically.

Do you have access to the machines running Azure SQL or SQL Server?

Azure SQL is a fully managed Platform-as-a-Service (PaaS) offering. When using SQL, you don’t have access to the machines that house your databases.

However, running SQL Server on-premise datacenter is comparable to running it on an azure virtual machine. Infrastructure-as-a-service(IaaS) is provided via Azure Virtual Machine.

How to export an SQL database from Azure?

  • Step 1: Open the page for your database in the Azure portal, then choose Export from the toolbar.
  • Step 2: Choose an existing Azure storage account and container for the export, provide the name of the BACPAC file(zip file containing data from the Database), and then enter the correct login information for the source database. 
  • Step 3: Select Ok after providing login credentials.
  • Step 4: Open the page for the server hosting the exported database to keep track of the progress of the export process. Select Import/Export history under Data management.


You have concluded the Azure SQL to SQL Server Migration by employing the import approach and the Data Migration Assistant tool. You can also assess and make recommendations to plan correctly and take action before the actual migration.

If you want to export data from a source of your choice, such as Azure SQL, into your desired Database/destination, such as SQL Server, then Hevo Data is the right choice for you! 

Want to take Hevo for a spin?

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Share your experience learning about the Azure SQL to SQL Server Migration in the comments below!

Roxana Raducanu
Freelance Technical Content Writer, Hevo Data

Roxana loves solving the intricacies of data integration and analysis to data teams by offering informative content to assist individuals in understanding these complex subjects.

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