Authentication for Databricks automation
In Databricks, authentication refers to verifying a Databricks identity (such as a user, service principal, or group). Databricks uses credentials (such as an access token or a username and password) to verify the identity.
After Databricks verifies the caller’s identity, Databricks then uses a process called authorization to determine whether the verified identity has sufficient access permissions to perform the specified action on the resource at the given location. This article includes details only about authentication. It does not include details about authorization or access permissions; see Authentication and access control.
When a tool makes an automation or API request, it includes credentials that authenticate an identity with Databricks. This article describes typical ways to create, store, and pass credentials and related information that Databricks needs to authenticate and authorize requests. To learn which credential types, related information, and storage mechanism are supported by your tools, SDKs, scripts, and apps, see your provider’s documentation.
Databricks account and workspace REST APIs
Databricks organizes its Databricks REST API into two categories of APIs: account APIs and workspace APIs. Each of these categories requires different sets of information to authenticate the target Databricks identity. Also, each supported Databricks authentication type requires additional information that uniquely identifies the target Databricks identity.
For instance, to authenticate a Databricks identity for calling Databricks account-level API operations, you must provide:
The target Databricks account console URL, which is typically
https://accounts.gcp.databricks.com
.The target Databricks account ID. See Locate your account ID.
Information that uniquely identifies the target Databricks identity for the target Databricks authentication type. For the specific information to provide, see the section later in this article for that authentication type.
To authenticate a Databricks identity for calling Databricks workspace-level API operations, you must provide:
The target Databricks workspace URL, for example
https://1234567890123456.7.gcp.databricks.com
.Information that uniquely identifies the target Databricks identity for the target Databricks authentication type. For the specific information to provide, see the section later in this article for that authentication type.
Databricks client unified authentication
Databricks provides a consolidated and consistent architectural and programmatic approach to authentication, known as Databricks client unified authentication. This approach helps make setting up and automating authentication with Databricks more centralized and predictable. It enables you to configure Databricks authentication once and then use that configuration across multiple Databricks tools and SDKs without further authentication configuration changes.
Participating Databricks tools and SDKs include:
The Databricks CLI
All participating tools and SDKs accept special environment variables as well as Databricks configuration profiles for authentication. The Databricks Terraform provider and the Databricks SDKs for Python, Java, and Go also accept direct configuration of authentication settings within code. For details, see the following sections and the tool’s or SDK’s documentation.
The following sections contain examples of how to configure your machine for authentication by using special environment variables, Databricks configuration profiles, Databricks Terraform provider code, and code for the Databricks SDKs for Python, Java, and Go. For other participating tools and SDKs:
The Databricks CLI supports special environment variables as well as Databricks configuration profiles for many authentication types. See the Environment and Profile examples in the following sections. See also Authentication for the Databricks CLI.
Databricks Connect supports multiple authentication configuration options that are unique to Databricks Connect. See Set up the client in the Databricks Connect documentation.
The Databricks extension for Visual Studio Code provides a unique user interface for configuring some authentication types and relies on its integration with Databricks Connect for some other authentication types. See Authentication for the Databricks extension for Visual Studio Code.
Databricks personal access token authentication
Databricks personal access tokens are one of the most well-supported types of credentials for resources and operations at the Databricks workspace level. Many storage mechanisms for credentials and related information, such as environment variables and Databricks configuration profiles, provide support for Databricks personal access tokens. Although users can have multiple personal access tokens in a Databricks workspace, each personal access token works for only a single Databricks workspace. The number of personal access tokens per user is limited to 600 per workspace.
Note
To learn whether Google ID tokens are supported by your tools, SDKs, scripts, and apps, see your provider’s documentation.
To automate Databricks account-level functionality, you cannot use Databricks personal access tokens. Instead, you use the Google ID account-level tokens of Databricks account-level admins. Databricks account-level admins are account-level Google service accounts acting as account-level admin users. For more information, see Authentication with Google ID tokens and the Account API. See also:
Databricks personal access tokens for workspace users
To create a Databricks personal access token for your Databricks workspace user, do the following:
In your Databricks workspace, click your Databricks username in the top bar, and then select User Settings from the dropdown.
Click Developer.
Next to Access tokens, click Manage.
Click Generate new token.
(Optional) Enter a comment that helps you to identify this token in the future, and change the token’s default lifetime of 90 days. To create a token with no lifetime (not recommended), leave the Lifetime (days) box empty (blank).
Click Generate.
Copy the displayed token to a secure location, and then click Done.
Be sure to save the copied token in a secure location. Do not share your copied token with others. If you lose the copied token, you cannot regenerate that exact same token. Instead, you must repeat this procedure to create a new token. If you lose the copied token, or you believe that the token has been compromised, Databricks strongly recommends that you immediately delete that token from your workspace by clicking the X next to the token on the Access tokens page.
Note
If you are not able to create or use tokens in your workspace, this might be because your workspace administrator has disabled tokens or has not given you permission to create or use tokens. See your workspace administrator or the following:
Databricks personal access tokens for service principals
To create a Databricks personal access token for a Databricks service principal instead of a Databricks workspace user, see Manage tokens for a service principal.
Note
If you are not able to create or use tokens in your workspace, this might be because your workspace administrator has disabled tokens or has not given you permission to create or use tokens. See your workspace administrator or the following:
Perform Databricks personal access token authentication
To configure Databricks personal access token authentication, you must set the following associated environment variables, .databrickscfg
fields, Terraform fields, or Config
fields:
The Databricks host, specified as the target Databricks workspace URL, for example
https://1234567890123456.7.gcp.databricks.com
The Databricks personal access token for the Databricks user account.
To perform Databricks personal access token authentication, integrate the following within your code, based on the participating tool or SDK:
To use environment variables with a tool or SDK, see the tool’s or SDK’s documentation. See also Environment variables and fields for client unified authentication and the Default order of evaluation for client unified authentication methods and credentials.
Set the following environment variables:
DATABRICKS_HOST
, set to the Databricks workspace URL, for examplehttps://1234567890123456.7.gcp.databricks.com
.DATABRICKS_TOKEN
Create or identify a Databricks configuration profile with the following fields in your .databrickscfg
file. If you create the profile, replace the placeholders with the appropriate values. To use the profile with a tool or SDK, see the tool’s or SDK’s documentation. See also Environment variables and fields for client unified authentication and the Default order of evaluation for client unified authentication methods and credentials.
Set the following values in your .databrickscfg
file. In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
[<some-unique-configuration-profile-name>]
host = <workspace-url>
token = <token>
provider "databricks" {
alias = "workspace"
}
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as HashiCorp Vault. See also Vault Provider). In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
provider "databricks" {
alias = "workspace"
host = <retrieve-workspace-url>
token = <retrieve-token>
}
from databricks.sdk import WorkspaceClient
w = WorkspaceClient()
# ...
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as Google Cloud Secret Manager). In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
from databricks.sdk import WorkspaceClient
w = WorkspaceClient(
host = retrieve_workspace_url(),
token = retrieve_token()
)
# ...
import com.databricks.sdk.WorkspaceClient;
// ...
WorkspaceClient w = new WorkspaceClient();
// ...
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as Google Cloud Secret Manager). In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
import com.databricks.sdk.WorkspaceClient;
import com.databricks.sdk.core.DatabricksConfig;
// ...
DatabricksConfig cfg = new DatabricksConfig()
.setHost(retrieveWorkspaceUrl())
.setToken(retrieveToken());
WorkspaceClient w = new WorkspaceClient(cfg);
// ...
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
w := databricks.Must(databricks.NewWorkspaceClient())
// ...
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as Google Cloud Secret Manager). In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
w := databricks.Must(databricks.NewWorkspaceClient(&databricks.Config{
Host: retrieveWorkspaceUrl(),
Token: retrieveToken(),
}))
// ...
Google Cloud credentials authentication
Google Cloud credentials authentication uses Google Cloud service account credentials to authenticate the target Google Cloud service account.
To create a Google Cloud service account, see Create service accounts in the Google Cloud documentation.
To add a Google Cloud service account to a Databricks account or workspace, add the service account as a Databricks user, and use the service account’s email address as the user’s username. (Google Cloud service accounts are separate from Databricks service principals.) See:
To generate a local Google Cloud service account key file, which Google Cloud needs to generate the Google Cloud credentials to authenticate, see Create a service account key in the Google Cloud documentation.
To configure Google Cloud credentials authentication with Databricks, you must set the following associated environment variables, .databrickscfg
fields, Terraform fields, or Config
fields:
The Databricks host.
For account operations, specify
https://accounts.gcp.databricks.com
.For workspace operations, specify the workspace URL, for example
https://1234567890123456.7.gcp.databricks.com
.
For account operations, the Databricks account ID.
The Google Cloud credentials, specified as the local path to the Google Cloud service account key file, or the contents of the service account key file in JSON format.
To perform Google Cloud credentials authentication with Databricks, integrate the following within your code, based on the participating tool or SDK:
To use environment variables with a tool or SDK, see the tool’s or SDK’s documentation. See also Environment variables and fields for client unified authentication and the Default order of evaluation for client unified authentication methods and credentials.
For account-level operations, set the following environment variables:
DATABRICKS_HOST
, set to the value of your Databricks account console URL,https://accounts.gcp.databricks.com
.DATABRICKS_ACCOUNT_ID
GOOGLE_CREDENTIALS
For workspace-level operations, set the following environment variables:
DATABRICKS_HOST
, set to the value of your Databricks workspace URL, for examplehttps://1234567890123456.7.gcp.databricks.com
.GOOGLE_CREDENTIALS
Create or identify a Databricks configuration profile with the following fields in your .databrickscfg
file. If you create the profile, replace the placeholders with the appropriate values. To use the profile with a tool or SDK, see the tool’s or SDK’s documentation. See also Environment variables and fields for client unified authentication and the Default order of evaluation for client unified authentication methods and credentials.
For account-level operations, set the following values in your .databrickscfg
file. In this case, the Databricks account console URL is https://accounts.gcp.databricks.com
:
[<some-unique-configuration-profile-name>]
host = <account-console-url>
account_id = <account-id>
google_credentials = <path-to-google-service-account-credentials-file>
For workspace-level operations, set the following values in your .databrickscfg
file. In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
[<some-unique-configuration-profile-name>]
host = <workspace-url>
google_credentials = <path-to-google-service-account-credentials-file>
For account-level operations, for default authentication:
provider "databricks" {
alias = "accounts"
}
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as HashiCorp Vault. See also Vault Provider). In this case, the Databricks account console URL is https://accounts.gcp.databricks.com
:
provider "databricks" {
alias = "accounts"
host = <retrieve-account-console-url>
account_id = <retrieve-account-id>
google_credentials = <retrieve-google-credentials>
}
For workspace-level operations, for default authentication:
provider "databricks" {
alias = "workspace"
}
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as HashiCorp Vault. See also Vault Provider). In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
provider "databricks" {
alias = "workspace"
host = <retrieve-workspace-url>
google_credentials = <retrieve-google-credentials>
}
Note
The Databricks SDK for Python has not yet implemented Google Cloud credentials authentication.
Note
The Databricks SDK for Java has not yet implemented Google Cloud credentials authentication.
For account-level operations, for default authentication:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
a := databricks.Must(databricks.NewAccountClient())
// ...
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as Google Cloud Secret Manager). In this case, the Databricks account console URL is https://accounts.gcp.databricks.com
:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
a := databricks.Must(databricks.NewAccountClient(&databricks.Config{
Host: retrieveAccountConsoleUrl(),
AccountId: retrieveAccountId(),
GoogleCredentials: retrieveGoogleCredentials(),
}))
// ...
For workspace-level operations, for default authentication:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
w := databricks.Must(databricks.NewWorkspaceClient())
// ...
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as Google Cloud Secret Manager). In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
w := databricks.Must(databricks.NewWorkspaceClient(&databricks.Config{
Host: retrieveWorkspaceUrl(),
GoogleCredentials: retrieveGoogleCredentials(),
}))
// ...
Google Cloud ID authentication
Google Cloud ID authentication uses the Google Cloud CLI to authenticate the target Google Cloud service account.
To create a Google Cloud service account, see Create service accounts in the Google Cloud documentation.
To add a Google Cloud service account to a Databricks account or workspace, add the service account as a Databricks user, and use the service account’s email address as the user’s username. (Google Cloud service accounts are separate from Databricks service principals.) See:
To configure Google Cloud ID authentication with Databricks, you must have the Google Cloud CLI installed locally. You must also set the following associated environment variables, .databrickscfg
fields, Terraform fields, or Config
fields:
The Databricks host.
For account operations, specify
https://accounts.gcp.databricks.com
.For workspace operations, specify the workspace URL, for example
https://1234567890123456.7.gcp.databricks.com
.
For account operations, the Databricks account ID.
The Google Cloud service account, specified as the service account’s email address.
To perform Google Cloud ID authentication with Databricks, integrate the following within your code, based on the participating tool or SDK:
To use environment variables with a tool or SDK, see the tool’s or SDK’s documentation. See also Environment variables and fields for client unified authentication and the Default order of evaluation for client unified authentication methods and credentials.
For account-level operations, set the following environment variables:
DATABRICKS_HOST
, set to the value of your Databricks account console URL,https://accounts.gcp.databricks.com
.DATABRICKS_ACCOUNT_ID
GOOGLE_SERVICE_ACCOUNT
For workspace-level operations, set the following environment variables:
DATABRICKS_HOST
, set to the value of your Databricks workspace URL, for examplehttps://1234567890123456.7.gcp.databricks.com
.GOOGLE_SERVICE_ACCOUNT
Create or identify a Databricks configuration profile with the following fields in your .databrickscfg
file. If you create the profile, replace the placeholders with the appropriate values. To use the profile with a tool or SDK, see the tool’s or SDK’s documentation. See also Environment variables and fields for client unified authentication and the Default order of evaluation for client unified authentication methods and credentials.
For account-level operations, set the following values in your .databrickscfg
file. In this case, the Databricks account console URL is https://accounts.gcp.databricks.com
:
[<some-unique-configuration-profile-name>]
host = <account-console-url>
account_id = <account-id>
google_service_account = <google-cloud-service-account-email-address>
For workspace-level operations, set the following values in your .databrickscfg
file. In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
[<some-unique-configuration-profile-name>]
host = <workspace-url>
google_service_account = <google-cloud-service-account-email-address>
For account-level operations, for default authentication:
provider "databricks" {
alias = "accounts"
}
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as HashiCorp Vault. See also Vault Provider). In this case, the Databricks account console URL is https://accounts.gcp.databricks.com
:
provider "databricks" {
alias = "accounts"
host = <retrieve-account-console-url>
account_id = <retrieve-account-id>
google_service_account = <retrieve-google-service-account>
}
For workspace-level operations, for default authentication:
provider "databricks" {
alias = "workspace"
}
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as HashiCorp Vault. See also Vault Provider). In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
provider "databricks" {
alias = "workspace"
host = <retrieve-workspace-url>
google_service_account = <retrieve-google-service-account>
}
Note
The Databricks SDK for Python has not yet implemented Google Cloud ID authentication.
Note
The Databricks SDK for Java has not yet implemented Google Cloud ID authentication.
For account-level operations, for default authentication:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
a := databricks.Must(databricks.NewAccountClient())
// ...
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as Google Cloud Secret Manager). In this case, the Databricks account console URL is https://accounts.gcp.databricks.com
:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
a := databricks.Must(databricks.NewAccountClient(&databricks.Config{
Host: retrieveAccountConsoleUrl(),
AccountId: retrieveAccountId(),
GoogleServiceAccount: retrieveGoogleServiceAccount(),
}))
// ...
For workspace-level operations, for default authentication:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
w := databricks.Must(databricks.NewWorkspaceClient())
// ...
For direct configuration (replace the retrieve
placeholders with your own implementation to retrieve the values from the console or some other configuration store, such as Google Cloud Secret Manager). In this case, the host is the Databricks workspace URL, for example https://1234567890123456.7.gcp.databricks.com
:
import (
"github.com/databricks/databricks-sdk-go"
)
// ...
w := databricks.Must(databricks.NewWorkspaceClient(&databricks.Config{
Host: retrieveWorkspaceUrl(),
GoogleServiceAccount: retrieveGoogleServiceAccount(),
}))
// ...
Default order of evaluation for client unified authentication methods and credentials
Whenever a participating tool or SDK needs to authenticate with Databricks, the tool or SDK tries the following types of authentication in the following order by default. When the tool or SDK succeeds with the type of authentication that it tries, the tool or SDK stops trying to authenticate with the remaining authentication types. To force an SDK to authenticate with a specific authentication type, set the Config
API’s Databricks authentication type field.
For each authentication type that the participating tool or SDK tries, the tool or SDK tries to find authentication credentials in the following locations, in the following order. When the tool or SDK succeeds in finding authentication credentials that can be used, the tool or SDK stops trying to find authentication credentials in the remaining locations.
Credential-related
Config
API fields (for SDKs). To setConfig
fields, see the SDK’s reference documentation.Credential-related environment variables. To set environment variables, see your operating system’s documentation.
Credential-related fields in the
DEFAULT
configuration profile within the.databrickscfg
file. To set configuration profile fields, see Databricks configuration profiles.Any related authentication credentials that are cached by the Google Cloud CLI. See Google Cloud CLI.
To provide maximum portability for your code, Databricks recommends that you create a custom configuration profile within the .databrickscfg
file, add the required fields for your target Databricks authentication type to the custom configuration profile, and then set the DATABRICKS_CONFIG_PROFILE
environment variable to the name of the custom configuration profile.
Environment variables and fields for client unified authentication
The following tables list the names and descriptions of the supported environment variables and fields for Databricks client unified authentication. In the following tables:
Environment variable, where applicable, is the name of the environment variable. To set environment variables, see your operating system’s documentation.
.databrickscfg
field, where applicable, is the name of the field within a Databricks configuration profiles file or Databricks Terraform configuration. To set.databrickscfg
fields, see Databricks configuration profiles.Terraform field, where applicable, is the name of the field within a Databricks Terraform configuration. To set Databricks Terraform fields, see Authentication in the Databricks Terraform provider documentation.
Config
field is the name of the field within theConfig
API for the specified SDK. To use theConfig
API, see the SDK’s reference documentation.
General host, token, and account ID environment variables and fields
Common name |
Description |
Environment variable |
|
|
---|---|---|---|---|
Databricks host |
(String) The Databricks host URL for either the Databricks workspace endpoint or the Databricks accounts endpoint. |
|
|
|
Databricks token |
(String) The Databricks personal access token. |
|
|
|
Databricks account ID |
(String) The Databricks account ID for the
Databricks account endpoint. Only has effect
when the Databricks host is also set to
|
|
|
|
Google Cloud-specific environment variables and fields
Common name |
Description |
Environment variable |
|
|
---|---|---|---|---|
Google Cloud service account |
(String) The Google Cloud service account’s e-mail address. |
|
|
|
Google Cloud credentials |
(String) The local path to the Google Cloud service account key file, or the contents of the service account key file in JSON format. |
|
|
|
.databrickscfg-specific environment variables and fields
Use these environment variables or fields to specify non-default settings for .databrickscfg
. See also Databricks configuration profiles.
Common name |
Description |
Environment variable |
Terraform field |
|
---|---|---|---|---|
|
(String) A non-default path to the
|
|
|
|
|
(String) The default named profile to
use, other than |
|
|
|
Authentication type field
Use this environment variable or field to force an SDK to use a specific type of Databricks authentication.
Common name |
Description |
Terraform field |
|
---|---|---|---|
Databricks authentication type |
(String) When multiple authentication attributes are available in the environment, use the authentication type specified by this argument. |
|
|
Supported Databricks authentication type field values include:
google-credentials
: Google Cloud credentials authenticationgoogle-id
: Google Cloud ID authentication
Databricks configuration profiles
A Databricks configuration profile (sometimes refered to as a configuration profile, a config profile, or simply a profile
) contains settings and other information that Databricks needs to authenticate. Databricks configuration profiles are stored in Databricks configuration profiles files for your tools, SDKs, scripts, and apps to use. To learn whether Databricks configuration profiles are supported by your tools, SDKs, scripts, and apps, see your provider’s documentation. All participating tools and SDKs that implement Databricks client unified authentication support Databricks configuration profiles.
To create a Databricks configuration profiles file:
Use your favorite text editor to create a file named
.databrickscfg
in your~
(your user home) folder on Unix, Linux, or macOS, or your%USERPROFILE%
(your user home) folder on Windows, if you do not already have one. Do not forget the dot (.
) at the beginning of the file name. Add the following contents to this file:[<some-unique-name-for-this-configuration-profile>] <field-name> = <field-value>
In the preceding contents, replace the following values, and then save the file:
<some-unique-name-for-this-configuration-profile>
with a unique name for the configuration profile, such asDEFAULT
,DEVELOPMENT
,PRODUCTION
, or similar. You can have multiple configuration profiles in the same.databrickscfg
file, but each configuration profile must have a unique name within this file.<field-name>
and<field-value>
with the name and a value for one of the required fields for the target Databricks authentication type. For the specific information to provide, see the section earlier in this article for that authentication type.Add a
<field-name>
and<field-value>
pair for each of the additional required fields for the target Databricks authentication type.
For example, for Databricks personal access token authentication, the .databrickscfg
file might look like this:
[DEFAULT]
host = https://1234567890123456.7.gcp.databricks.com
token = dapi123...
To create additional configuration profiles, specify different profile names within the same .databrickscfg
file. For example, to specify separate Databricks workspaces, each with their own Databricks personal access token:
[DEFAULT]
host = https://1234567890123456.7.gcp.databricks.com
token = dapi123...
[DEVELOPMENT]
host = https://2345678901234567.8.gcp.databricks.com
token = dapi234...
You can also specify different profile names within the .databrickscfg
file for Databricks accounts and different Databricks authentication types, for example:
[DEFAULT]
host = https://1234567890123456.7.gcp.databricks.com
token = dapi123...
[DEVELOPMENT]
host = https://2345678901234567.8.gcp.databricks.com
google_service_account = someone@example.com
ODBC DSNs
In ODBC, a data source name (DSN) is a symbolic name that tools, SDKs, scripts, and apps use to request a connection to an ODBC data source. A DSN stores connection details such as the path to an ODBC driver, networking details, authentication credentials, and database details. To learn whether ODBC DSNs are supported by your tools, scripts, and apps, see your provider’s documentation.
To install and configure the Databricks ODBC Driver and create an ODBC DSN for Databricks, see ODBC driver.
JDBC connection URLs
In JDBC, a connection URL is a symbolic URL that tools, SDKs, scripts, and apps use to request a connection to a JDBC data source. A connection URL stores connection details such as networking details, authentication credentials, database details, and JDBC driver capabilities. To learn whether JDBC connection URLs are supported by your tools, SDKs, scripts, and apps, see your provider’s documentation.
To install and configure the Databricks JDBC Driver and create a JDBC connection URL for Databricks, see JDBC driver.
Google Cloud CLI
The Google Cloud CLI enables you to authenticate with Databricks on Google Cloud through your terminal for Linux or macOS, or through PowerShell or your Command Prompt for Windows. To learn whether the Google Cloud CLI is supported by your tools, SDKs, scripts, and apps, see your provider’s documentation.
To use the Google Cloud CLI to authenticate with Databricks on Google Cloud manually, run the gcloud init command, and then follow the on-screen prompts:
gcloud init
For more detailed authentication options, see Initializing the gcloud CLI.
Note that tools and SDKs that implement the Databricks client unified authentication standard and that rely on the Google Cloud CLI should run the Google Cloud CLI automatically on your behalf to create and manage Databricks authentication.