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Applies to: SQL Server (all supported versions) - Linux

Note

The examples shown below use the docker.exe but most of these commands also work with Podman. It provides the CLI similar to Docker container Engine. You can read more about podman here.

In this quickstart, you use Docker to pull and run the SQL Server 2017 container image, mssql-server-linux. Then connect with sqlcmd to create your first database and run queries.

Tip

If you want to run SQL Server 2019 containers, see the SQL Server 2019 version of this article.

Note

Starting with SQL Server 2019 CU3, Ubuntu 18.04 is supported.
Starting with SQL Server 2019 CU10, Ubuntu 20.04 is supported.

In this quickstart, you use Docker to pull and run the SQL Server 2019 container image, mssql-server. Then connect with sqlcmd to create your first database and run queries.

Tip

This quickstart creates SQL Server 2019 containers. If you prefer to create SQL Server 2017 containers, see the SQL Server 2017 version of this article.

This image consists of SQL Server running on Linux based on Ubuntu 20.04. It can be used with the Docker Engine 1.8+ on Linux or on Docker for Mac/Windows. This quickstart specifically focuses on using the SQL Server on Linux image. The Windows image is not covered, but you can learn more about it on the mssql-server-windows-developer Docker Hub page.

Prerequisites

Docker Engine 1.8+ on any supported Linux distribution or Docker for Mac/Windows. For more information, see Install Docker. For more information on hardware requirements and processor support, see SQL Server 2019: Hardware and software requirements.
Docker overlay2 storage driver. This is the default for most users. If you find that you are not using this storage provider and need to change, see the instructions and warnings in the docker documentation for configuring overlay2.
Minimum of 2 GB of disk space.
Minimum of 2 GB of RAM.
System requirements for SQL Server on Linux.

Pull and run the 2017 container image

Before starting the following steps, make sure that you have selected your preferred shell (bash, PowerShell, or cmd) at the top of this article.

Pull the SQL Server 2017 Linux container image from Microsoft Container Registry.
Tip
If you want to run SQL Server 2019 containers, see the SQL Server 2019 version of this article.
The previous command pulls the latest SQL Server 2017 container image. If you want to pull a specific image, you add a colon and the tag name (for example, mcr.microsoft.com/mssql/server:2017-GA-ubuntu). To see all available images, see the mssql-server Docker hub page.
For the bash commands in this article, sudo is used. On macOS, sudo might not be required. On Linux, if you do not want to use sudo to run Docker, you can configure a docker group and add users to that group. For more information, see Post-installation steps for Linux.

To run the container image with Docker, you can use the following command from a bash shell (Linux/macOS) or elevated PowerShell command prompt.

Note

If you are using PowerShell Core, replace the double quotes with single quotes.

Note

The password should follow the SQL Server default password policy, otherwise the container can not setup SQL server and will stop working. By default, the password must be at least 8 characters long and contain characters from three of the following four sets: Uppercase letters, Lowercase letters, Base 10 digits, and Symbols. You can examine the error log by executing the docker logs command.

By default, this creates a container with the Developer edition of SQL Server 2017. The process for running production editions in containers is slightly different. For more information, see Run production container images.

The following table provides a description of the parameters in the previous docker run example:

Parameter	Description
-e 'ACCEPT_EULA=Y'	Set the ACCEPT_EULA variable to any value to confirm your acceptance of the End-User Licensing Agreement. Required setting for the SQL Server image.
-e 'SA_PASSWORD=<YourStrong@Passw0rd>'	Specify your own strong password that is at least 8 characters and meets the SQL Server password requirements. Required setting for the SQL Server image.
-p 1433:1433	Map a TCP port on the host environment (first value) with a TCP port in the container (second value). In this example, SQL Server is listening on TCP 1433 in the container and this is exposed to the port, 1433, on the host.
--name sql1	Specify a custom name for the container rather than a randomly generated one. If you run more than one container, you cannot reuse this same name.
-h sql1	Used to explicitly set the container hostname, if you don't specify it, it defaults to the container ID which is a randomly generated system GUID.
-d	Run the container in the background (daemon)
mcr.microsoft.com/mssql/server:2017-latest	The SQL Server 2017 Linux container image.

To view your Docker containers, use the docker ps command.
You should see output similar to the following screenshot:
If the STATUS column shows a status of Up, then SQL Server is running in the container and listening on the port specified in the PORTS column. If the STATUS column for your SQL Server container shows Exited, see the Troubleshooting section of the configuration guide. It will be ready for connection, once the SQL Server error logs display the message: SQL Server is now ready for client connections. This is an informational message; no user action is required. You can review the SQL Server error log inside the container using the command:

The -h (host name) parameter as discussed above, changes the internal name of the container to a custom value. This is the name you'll see returned in the following Transact-SQL query:

Setting -h and --name to the same value is a good way to easily identify the target container.

As a final step, change your SA password because the SA_PASSWORD is visible in ps -eax output and stored in the environment variable of the same name. See steps below.

Pull and run the 2019 container image

Before starting the following steps, make sure that you have selected your preferred shell (bash, PowerShell, or cmd) at the top of this article.

Pull the SQL Server 2019 Linux container image from Microsoft Container Registry.
Note
If you are using PowerShell Core, replace the double quotes with single quotes.
Tip
This quickstart uses the SQL Server 2019 Docker image. If you want to run the SQL Server 2017 image, see the SQL Server 2017 version of this article.
The previous command pulls the SQL Server 2019 container image based on Ubuntu. To instead use container images based on RedHat, see Run RHEL-based container images. To see all available images, see the mssql-server-linux Docker hub page.
For the bash commands in this article, sudo is used. On macOS, sudo might not be required. On Linux, if you do not want to use sudo to run Docker, you can configure a docker group and add users to that group. For more information, see Post-installation steps for Linux.

To run the container image with Docker, you can use the following command from a bash shell (Linux/macOS) or elevated PowerShell command prompt.

Note

By default, this creates a container with the Developer edition of SQL Server 2019.

The following table provides a description of the parameters in the previous docker run example:

Parameter	Description
-e 'ACCEPT_EULA=Y'	Set the ACCEPT_EULA variable to any value to confirm your acceptance of the End-User Licensing Agreement. Required setting for the SQL Server image.
-e 'SA_PASSWORD=<YourStrong@Passw0rd>'	Specify your own strong password that is at least 8 characters and meets the SQL Server password requirements. Required setting for the SQL Server image.
-p 1433:1433	Map a TCP port on the host environment (first value) with a TCP port in the container (second value). In this example, SQL Server is listening on TCP 1433 in the container and this is exposed to the port, 1433, on the host.
--name sql1	Specify a custom name for the container rather than a randomly generated one. If you run more than one container, you cannot reuse this same name.
-h sql1	Used to explicitly set the container hostname, if you don't specify it, it defaults to the container ID which is a randomly generated system GUID.
mcr.microsoft.com/mssql/server:2019-latest	The SQL Server 2019 Ubuntu Linux container image.

To view your Docker containers, use the docker ps command.
You should see output similar to the following screenshot:
If the STATUS column shows a status of Up, then SQL Server is running in the container and listening on the port specified in the PORTS column. If the STATUS column for your SQL Server container shows Exited, see Troubleshooting SQL Server Docker containers.

The -h (host name) parameter as discussed above, changes the internal name of the container to a custom value. This changes the internal name of the container to a custom value. This is the name you'll see returned in the following Transact-SQL query:

Setting -h and --name to the same value is a good way to easily identify the target container.

As a final step, change your SA password because the SA_PASSWORD is visible in ps -eax output and stored in the environment variable of the same name. See steps below.

Change the SA password

The SA account is a system administrator on the SQL Server instance that gets created during setup. After creating your SQL Server container, the SA_PASSWORD environment variable you specified is discoverable by running echo $SA_PASSWORD in the container. For security purposes, change your SA password.

Choose a strong password to use for the SA user.
Use docker exec to run sqlcmd to change the password using Transact-SQL. In the following example, replace the old password, <YourStrong!Passw0rd>, and the new password, <YourNewStrong!Passw0rd>, with your own password values.

Connect to SQL Server

The following steps use the SQL Server command-line tool, sqlcmd, inside the container to connect to SQL Server.

Use the docker exec -it command to start an interactive bash shell inside your running container. In the following example sql1 is name specified by the --name parameter when you created the container.
Once inside the container, connect locally with sqlcmd. Sqlcmd is not in the path by default, so you have to specify the full path.
Tip
You can omit the password on the command-line to be prompted to enter it.
If successful, you should get to a sqlcmd command prompt: 1>.

Create and query data

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The following sections walk you through using sqlcmd and Transact-SQL to create a new database, add data, and run a query.

Create a new database

The following steps create a new database named TestDB.

From the sqlcmd command prompt, paste the following Transact-SQL command to create a test database:
On the next line, write a query to return the name of all of the databases on your server:
The previous two commands were not executed immediately. Type GO on a new line to execute the previous commands:

Insert data

Next create a new table, Inventory, and insert two new rows.

From the sqlcmd command prompt, switch context to the new TestDB database:
Create new table named Inventory:
Insert data into the new table:
Type GO to execute the previous commands:

Select data

Now, run a query to return data from the Inventory table.

From the sqlcmd command prompt, enter a query that returns rows from the Inventory table where the quantity is greater than 152:
Execute the command:

Exit the sqlcmd command prompt

To end your sqlcmd session, type QUIT:
To exit the interactive command-prompt in your container, type exit. Your container continues to run after you exit the interactive bash shell.

Connect from outside the container

You can also connect to the SQL Server instance on your Docker machine from any external Linux, Windows, or macOS tool that supports SQL connections.

The following steps use sqlcmd outside of your container to connect to SQL Server running in the container. These steps assume that you already have the SQL Server command-line tools installed outside of your container. The same principles apply when using other tools, but the process of connecting is unique to each tool.

Find the IP address for the machine that hosts your container. On Linux, use ifconfig or ip addr. On Windows, use ipconfig.
For this example, install the sqlcmd tool on your client machine. For more information, see Install sqlcmd on Windows or Install sqlcmd on Linux.
Run sqlcmd specifying the IP address and the port mapped to port 1433 in your container. In this example, that is the same port, 1433, on the host machine. If you specified a different mapped port on the host machine, you would use it here. You will also need to open the appropriate inbound port on your firewall to allow the connection.
Run Transact-SQL commands. When finished, type QUIT.

Other common tools to connect to SQL Server include:

Remove your container

If you want to remove the SQL Server container used in this tutorial, run the following commands:

Warning

Stopping and removing a container permanently deletes any SQL Server data in the container. If you need to preserve your data, create and copy a backup file out of the container or use a container data persistence technique.

Docker demo

After you have tried using the SQL Server container image for Docker, you might want to know how Docker is used to improve development and testing. The following video shows how Docker can be used in a continuous integration and deployment scenario.

Next steps

For a tutorial on how to restore database backup files into a container, see Restore a SQL Server database in a Linux Docker container. Explore other scenarios, such as running multiple containers, data persistence, and troubleshooting.

Also, check out the mssql-docker GitHub repository for resources, feedback, and known issues.

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Azure Data Studio runs on Windows, macOS, and Linux.

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Download and install the latest release:

Note

If you're updating from SQL Operations Studio and want to keep your settings, keyboard shortcuts, or code snippets, see Move user settings.

Platform	Download	Release date	Version
Windows	User Installer (recommended) System Installer .zip	March 18, 2020	1.16.0
macOS	.zip	March 18, 2020	1.16.0
Linux	.deb .rpm .tar.gz	March 18, 2020	1.16.0

For details about the latest release, see the release notes.

Get Azure Data Studio for Windows

This release of Azure Data Studio includes a standard Windows installer experience, and a .zip file.

The user installer is recommended because it does not require administrator privileges, which simplifies both installs and upgrades. The user installer does not require Administrator privileges as the location is under your user Local AppData (LOCALAPPDATA) folder. The user installer also provides a smoother background update experience. For more information, see User setup for Windows.

User Installer (recommended)

Download and run the Azure Data Studio user installer for Windows.
Start the Azure Data Studio app.

System Installer

Download and run the Azure Data Studio system installer for Windows.
Start the Azure Data Studio app.

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.zip file

Download Azure Data Studio .zip for Windows.
Browse to the downloaded file and extract it.
Run azuredatastudio-windowsazuredatastudio.exe

Get Azure Data Studio for macOS

Download Azure Data Studio for macOS.
To expand the contents of the zip, double-click it.
To make Azure Data Studio available in the Launchpad, drag Azure Data Studio.app to the Applications folder.

Get Azure Data Studio for Linux

Download Azure Data Studio for Linux by using one of the installers or the tar.gz archive:
To extract the file and launch Azure Data Studio, open a new Terminal window and type the following commands:
Debian Installation:
rpm Installation:
tar.gz Installation:
Note
On Debian, Redhat, and Ubuntu, you may have missing dependencies. Use the following commands to install these dependencies depending on your version of Linux:
Debian:
Redhat:
Ubuntu:

Download Insiders build of Azure Data Studio

In general, users should download the stable release of Azure Data Studio above. However, if you want to try out our beta features and give us feedback, you can download an Insiders build of Azure Data Studio.

Uninstall Azure Data Studio

If you installed Azure Data Studio using the Windows installer, then uninstall the same way you remove any Windows application.

If you installed Azure Data Studio with a .zip or other archive, then simply delete the files.

Supported Operating Systems

Azure Data Studio runs on Windows, macOS, and Linux, and is supported on the following platforms:

Windows

Windows 10 (64-bit)
Windows 8.1 (64-bit)
Windows 8 (64-bit)
Windows 7 (SP1) (64-bit) - Requires KB2533623
Windows Server 2019
Windows Server 2016
Windows Server 2012 R2 (64-bit)
Windows Server 2012 (64-bit)
Windows Server 2008 R2 (64-bit)

macOS

macOS 10.15 Catalina
macOS 10.14 Mojave
macOS 10.13 High Sierra
macOS 10.12 Sierra

Linux

Red Hat Enterprise Linux 7.4
Red Hat Enterprise Linux 7.3
SUSE Linux Enterprise Server v12 SP2
Ubuntu 16.04

Recommended System Requirements

CPU Cores	Memory/RAM
Recommended	4	8 GB
Minimum	2	4 GB

Check for updates

To check for latest updates, click the gear icon on the bottom left of the window and click Check for Updates

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Supported SQL offerings

This version of Azure Data Studio works with all supported versions of SQL Server 2014 - SQL Server 2019 (15.x) and provides support for working with the latest cloud features in Azure SQL Database and Azure SQL Data Warehouse. Azure Data Studio also provides preview support for Azure SQL Managed Instance.

Upgrade from SQL Operations Studio

If you are still using SQL Operations Studio, you need to upgrade to Azure Data Studio. SQL Operations Studio was the preview name and preview version of Azure Data Studio. In September 2018, we changed the name to Azure Data Studio and released the General Availability (GA) version. Because SQL Operations Studio is no longer being updated or supported, we ask all SQL Operations Studio users to download the latest version of Azure Data Studio to get the latest features, security updates, and fixes.

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When upgrading from the old preview to the latest Azure Data Studio, you will lose your current settings and extensions. To move your settings, follow the instructions in the following Move user settings section:

Move user settings

If you want to move your custom settings, keyboard shortcuts, or code snippets, follow the steps below. This is important to do if you are upgrading from SQL Operations Studio version to Azure Data Studio.

If you already have Azure Data Studio, or you've never installed or customized SQL Operations Studio, then you can ignore this section.

Open Settings by clicking the gear on the bottom left and clicking Settings.
Right-click the User Settings tab on top and click Reveal in Explorer
Copy all files in this folder and save in an easy to find location on your local drive, like your Documents folder.
In your new version of Azure Data Studio, follow steps 1-2, then for step 3 paste the contents you saved into the folder. You can also manually copy over the settings, keybindings, or snippets in their respective locations.
If overriding an existing installation, delete the old install directory before installation to avoid errors connecting to your Azure account for the resource explorer.

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Next Steps

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See one of the following quickstarts to get started:

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