Share via

Create a workspace

This article is an overview of your options for creating and managing workspaces.

What is a workspace?

A workspace is a Azure Databricks deployment in a cloud service account. It provides a unified environment for working with Azure Databricks assets for a specified set of users.

There are two types of Databricks workspaces available:

  • Serverless workspaces: A workspace deployment in your Azure Databricks account that comes pre-configured with serverless compute and default storage to provide a completely serverless experience. You can still connect to your cloud storage from serverless workspaces.
  • Hybrid workspaces: Also referred to as a Classic workspace, this workspace deployment provisions storage and compute resources in your existing Azure account. Serverless compute is still available in hybrid workspaces.

Requirements

Before you create an Azure Databricks workspace, you must have an Azure subscription that isn't a Free Trial Subscription.

If you have a free account, complete the following steps:

  1. Go to your profile and change your subscription to pay-as-you-go. See Azure free account.
  2. Remove the spending limit.
  3. Request a quota increase for vCPUs in your region.

Required Azure permissions

To create a Azure Databricks workspace, you must be the one of the following:

  • A user with the Azure Contributor or Owner role at the subscription level.
  • A user with a custom role definition that has the following list of permissions:
    • Microsoft.Databricks/workspaces/*
    • Microsoft.Resources/subscriptions/resourceGroups/read
    • Microsoft.Resources/subscriptions/resourceGroups/write
    • Microsoft.Databricks/accessConnectors/*
    • Microsoft.Compute/register/action
    • Microsoft.ManagedIdentity/register/action
    • Microsoft.Storage/register/action
    • Microsoft.Network/register/action
    • Microsoft.Resources/deployments/validate/action
    • Microsoft.Resources/deployments/write
    • Microsoft.Resources/deployments/read

Note

The Microsoft.Compute/register/action, Microsoft.ManagedIdentity/register/action, Microsoft.Storage/register/action, Microsoft.Network/register/action permissions are not required if these providers are already registered in the subscription. See Register resource provider.

Choosing a workspace type

The following sections describe which workspace type is best for common use cases. Use these recommendations to help you decide whether to deploy a serverless or a classic workspace.

When to choose serverless workspaces

Serverless workspaces are the best choice for most use cases and the easiest way to get started with operational and consumer use cases, such as Lakebase, Genie, and Databricks Apps.

Serverless workspaces are the best choice for the following use cases:

  • Enabling business users to access Databricks One
  • Creating AI/BI dashboards
  • Creating Databricks Apps
  • Performing exploratory analytics using notebooks or SQL warehouses
  • Connecting to SaaS providers through Lakehouse Federation (but not Lakeflow Connect)
  • Using Genie Spaces for business use cases
  • Using AI features such as vector search, model serving, AI functions, and Agent Bricks
  • Creating serverless Lakeflow Spark Declarative Pipelines

When to choose classic workspaces

Classic workspaces are the best choice for the following use cases:

  • Porting existing legacy Spark code that uses Spark RDDs
  • Using Scala or R as your primary coding language
  • Streaming data that requires time-based trigger intervals
  • Connecting to on-premises systems or private databases directly, through Lakeflow Connect

Workspace creation options

There are multiple ways to deploy an Azure Databricks workspace. The standard deployment method is through the Azure Portal or Terraform.

Additionally, you can create workspaces using the following tools:

  • Last updated on