Install SQL Server 2019 big data tools

THIS TOPIC APPLIES TO:yesSQL Server (starting with 2019)noAzure SQL DatabasenoAzure SQL Data Warehouse noParallel Data Warehouse

This article describes the client tools that should be installed for creating, managing, and using SQL Server 2019 big data clusters (preview). The following section provides a list of tools and links to installation instructions. Before deploying a big data cluster, configure the tools marked required on Windows or Linux.


SQL Server big data clusters is first available as a limited public preview through the SQL Server 2019 Early Adoption Program. To request access, register here, and specify your interest to try SQL Server big data clusters. Microsoft will triage all requests and respond as soon as possible.

Big data cluster tools

The following table lists common big data cluster tools and how to install them:

Tool Required Description Installation
mssqlctl Yes Command-line tool for installing and managing a big data cluster. Install
kubectl1 Yes Command-line tool for monitoring the underlying Kuberentes cluster (More info). Windows | Linux
Azure Data Studio Yes Cross-platform graphical tool for querying SQL Server (More info). Install
SQL Server 2019 extension Yes Extension for Azure Data Studio that supports connecting to the big data cluster. Also provides a Data Virtualization wizard. Install
Azure CLI2 For AKS Modern command-line interface for managing Azure services. Used with AKS big data cluster deployments (More info). Install
mssql-cli Optional Modern command-line interface for querying SQL Server (More info). Windows | Linux
sqlcmd For some scripts Legacy command-line tool for querying SQL Server (More info). Windows | Linux
curl 3 For some scripts Command-line tool for transferring data with URLs. Windows | Linux: install curl package

1 You must use kubectl version 1.10 or later. Also, the version of kubectl should be plus or minus one minor version of your Kubernetes cluster. If you want to install a specific version on kubectl client, see Install kubectl binary via curl (on Windows 10, use cmd.exe and not Windows PowerShell to run curl).


To use kubectl with a previously deployed cluster on Azure Kubernetes Service (AKS), you must set the cluster context with the following Azure CLI command:

az aks get-credentials --name <aks_cluster_name> --resource-group <azure_resource_group_name>

2 You must be using Azure CLI version 2.0.4 or later. Run az --version to find the version if needed.

3 If you are running on Windows 10, curl is already in your PATH when running from a cmd prompt. For other versions of Windows, download curl using the link and place it in your PATH.

Which tools are required?

The previous table provides all of the common tools that are used with big data clusters. Which tools are required depends on your scenario. But in general, the following tools are most important for managing, connecting to, and querying the cluster:

  • mssqlctl
  • kubectl
  • Azure Data Studio
  • SQL Server 2019 extension

The remaining tools are only required in certain scenarios. Azure CLI can be used to manage Azure services associated with AKS deployments. mssql-cli is an optional but useful tool that allows you to connect to the SQL Server master instance in the cluster and run queries from the command line. And sqlcmd and curl are required if you plan to install sample data with the GitHub script.

Next steps

After configuring the tools, deploy a SQL Server 2019 big data cluster to Kubernetes in the Cloud or on-premises. For more information, see the following deployment articles:

For More info about big data clusters, see What are SQL Server 2019 big data clusters?.