This feature is currently supported for Databricks, Snowflake, Redshift, and BigQuery.
OAuth support empowers users to run data diffs based on their individual permissions and roles configured within the data warehouses. This ensures that data access is governed by existing security policies and protocols.

​
How it works

​
1. Create a Data Diff

When you attempt to run a data diff, you will notice that it won’t run without authentication:

​
2. Authorize the Data Diff

Authorize the data diff by clicking the Authenticate button. This will redirect you to the data warehouse for authentication:
Upon successful authentication, you will be redirected back.

​
3. The Data Diff is now running

​
4. View the Data Diff results

The results reflect your permissions within the data warehouse:
Note that running the same data diff, as a different user, renders different results:
The masked values represent the data retrieved from the data warehouse. We do not conduct any post-processing:
By default, results are only visible for their authors. Users can still clone the data diffs, but the results might be different depending on their data warehouse access levels. For example, as a different user, I won’t be able to access the data diff results for Filip’s data diff:

​
5. Sharing Data Diffs

Data diff sharing is a feature that enables you to share data diffs with other users. This is useful in scenarios such as compliance verification, where auditors can access specific data diffs without first requiring permissions to be set up in the data warehouse. Sharing can be accessed via the Actions dropdown on the data diff page:
Note that data diff sharing is disabled by default:
It can be enabled under Org Settings by clicking on Allow Data Diff sharing:
Once enabled, you can share data diffs with other users:

​
Configuring OAuth

Navigate to Settings and click on your data connection. Then, click on Advanced settings and under OAuth, set the Client Id and Client Secret fields:

​
Example: Databricks

To create a new Databricks app connection:
  1. Go to Settings and App connections.
  2. Click Add connection in the top right of the screen.
  1. Fill in the required fields:
Application Name: 
Datafold OAuth connection
Redirect URLs: 
https://app.datafold.com/api/internal/oauth_dwh/callback
INFODatafold caches access tokens and using refresh tokens fetches new valid tokens in order to complete the diffs and reduce the number of times users need to authenticate against the data warehouses.One hour is sufficient for the access token.The refresh token will determine the frequency of user reauthentication, whether it’s daily, weekly, or monthly.

​
3. Click Add to obtain the Client ID and Client Secret

​
4. Fill in the Client ID and Client Secret fields in Datafold’s Data Connection advanced settings:

​
5. Click Test and save OAuth

You will be redirected to Databricks to complete authentication. If you are already authenticated, you will be redirected back. This notification signals a successful OAuth configuration:

​
Additional steps for Databricks

To ensure that users have correct access rights to temporary tables (stored in Dataset for temporary tables provided in the Basic settings for the Databricks connection), follow these steps:
  1. Update the permissions for the Dataset for temporary tables in Databricks.
  2. Grant these permissions to Datafold users: USE SCHEMA and CREATE TABLE.
This will ensure that materialization results from data diffs are only readable by their authors.

​
Example: Snowflake

To create a new Snowflake app connection:
  1. Go to Snowflake and run this SQL:
CREATE SECURITY INTEGRATION DATAFOLD_OAUTH
TYPE = OAUTH
ENABLED = TRUE
OAUTH_CLIENT = CUSTOM
OAUTH_CLIENT_TYPE = 'CONFIDENTIAL'
OAUTH_REDIRECT_URI = 'https://app.datafold.com/api/internal/oauth_dwh/callback'
PRE_AUTHORIZED_ROLES_LIST=(<ROLENAME1>, <ROLENAME2>, ...)
OAUTH_ISSUE_REFRESH_TOKENS = TRUE
OAUTH_REFRESH_TOKEN_VALIDITY = 604800
OAUTH_ENFORCE_PKCE=TRUE;
It should result in this message:
CAUTION
  • PRE_AUTHORIZED_ROLES_LIST must include all roles allowed to use the current security integration.
  • By default, ACCOUNTADMIN, SECURITYADMIN, and ORGADMIN are not allowed to be included in PRE_AUTHORIZED_ROLES_LIST.
INFODatafold caches access tokens and uses refresh tokens to fetch new valid tokens in order to complete the diffs and reduce the number of times users need to authenticate against the data warehouses.OAUTH_REFRESH_TOKEN_VALIDITY can be in the range of 3600 (1 hour) to 7776000 (90 days).
  1. To retrieve OAUTH_CLIENT_ID and OAUTH_CLIENT_SECRET, run the following SQL:
select system$show_oauth_client_secrets('DATAFOLD_OAUTH');

​
Example result:

  1. Fill in the Client ID and Client Secret fields in Datafold’s Data Connection advanced settings:
  1. Click Test and save OAuth
You will be redirected to Snowflake to complete authentication. info Your default Snowflake role will be used for the generated access token. This notification signals a successful OAuth configuration:

​
Additional steps for Snowflake

To guarantee correct access rights to temporary tables (stored in Dataset for temporary tables provided in the Basic settings for Snowflake connection):
  • Grant the required privileges on the database and TEMP schema for all roles that will be using the OAuth flow. This must be done for all roles that will be utilizing the OAuth flow.
GRANT USAGE ON WAREHOUSE <WH_NAME> TO ROLE <ROLENAME>;
GRANT USAGE ON DATABASE <DB_NAME> TO ROLE <ROLENAME>;
GRANT USAGE ON ALL SCHEMAS IN DATABASE <DB_NAME> TO ROLE <ROLENAME>;
GRANT USAGE ON FUTURE SCHEMAS IN DATABASE <DB_NAME> TO ROLE <ROLENAME>;
GRANT ALL ON SCHEMA <DB_NAME>.<TEMP_SCHEMA_NAME> TO ROLE <ROLENAME>;
  • Revoke SELECT privileges for tables in the TEMP schema for all roles that will be using the OAuth flow (except for the DATAFOLDROLE role), if they were provided. This action must be performed for all roles utilizing the OAuth flow..
-- Revoke SELECT privileges for the TEMP SCHEMA
revoke SELECT ON ALL TABLES IN SCHEMA <DB_NAME>.<TEMP_SCHEMA_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON FUTURE TABLES IN SCHEMA <DB_NAME>.<TEMP_SCHEMA_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON ALL VIEWS IN SCHEMA <DB_NAME>.<TEMP_SCHEMA_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON FUTURE VIEWS IN SCHEMA <DB_NAME>.<TEMP_SCHEMA_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON ALL MATERIALIZED VIEWS IN SCHEMA <DB_NAME>.<TEMP_SCHEMA_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON FUTURE MATERIALIZED VIEWS IN SCHEMA <DB_NAME>.<TEMP_SCHEMA_NAME> FROM ROLE <ROLENAME>;
-- Revoke SELECT privileges for a Database
revoke SELECT ON ALL TABLES IN DATABASE <DB_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON FUTURE TABLES IN DATABASE <DB_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON ALL VIEWS IN DATABASE <DB_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON FUTURE VIEWS IN DATABASE <DB_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON ALL MATERIALIZED VIEWS IN DATABASE <DB_NAME> FROM ROLE <ROLENAME>;
revoke SELECT ON FUTURE MATERIALIZED VIEWS IN DATABASE <DB_NAME> FROM ROLE <ROLENAME>;
CAUTIONIf one of the roles will have FUTURE GRANTS at the database level, this role will also will have FUTURE GRANTS on the TEMP schema.

​
Example: Redshift

Redshift does not support OAuth2. To execute data diffs on behalf of a specific user, that user needs to provide their own credentials to Redshift.
  1. Configure permissions on the Redshift side. Grant the necessary access rights to temporary tables (stored in the Dataset for temporary tables provided in the Basic settings for Redshift connection):
GRANT USAGE on SCHEMA <TEMP_SCHEMA_NAME> to <USERNAME>;
GRANT CREATE on SCHEMA <TEMP_SCHEMA_NAME> to <USERNAME>;
  1. As an Administrator, select the Enabled toggle in Datafold’s Redshift Data Connection Advanced settings:
Then, click the Test and Save button.
  1. As a User, add your Redshift credentials into Datafold. Click on your Datafold username to Edit Profile:
Then, click Add credentials and select the required Redshift data connection from the Data Connections list:
Finally, provide your Redshift username and password, and configure the Delete on field (after this date, your credentials will be removed from Datafold):
Click Create credentials.

​
Example: BigQuery

  1. To create a new Google Cloud OAuth 2.0 Client ID, go to the Google Cloud console, navigate to APIs & Services, then Credentials, and click + CREATE CREDENTIALS:
Select OAuth client ID:
From the list of Application type, select Web application:
Provide a name in the Name field:
In Authorized redirect URIs, provide https://app.datafold.com/api/internal/oauth_dwh/callback:
Click CREATE. Then, download the OAuth Client credentials as a JSON file:
  1. Activate BigQuery OAuth in Datafold by uploading the JSON OAuth credentials in the JSON OAuth keys file section, in Datafold’s BigQuery Data Connection Advanced settings:
Click Test and Save.

​
Additional steps for BigQuery

  1. Create a new temporary schema (dataset) for each OAuth user.
Go to Google Cloud console, navigate to BigQuery, select your project in BigQuery, and click on Create dataset:
Provide datafold_tmp_<username> as the Dataset ID and set the same region as configured for other datasets. Click CREATE DATASET:
  1. Configure permissions for datafold_tmp_<username>.
Grant read/write/create/delete permissions to the user for their datafold_tmp_<username> schema. This can be done by granting roles like BigQuery Data Editor or BigQuery Data Owner or any custom roles with the required permissions. Go to Google Cloud console, navigate to BigQuery, select datafold_tmp_<username> dataset, and click Create dataset → Manage Permissions:
Click + ADD PRINCIPAL, specify the user and role, then click SAVE:
caution Ensure that only the specified user (excluding admins) has read/write/create/delete permissions on datafold_tmp_<username>.
  1. Configure temporary schema in Datafold.
As a user, navigate to https://app.datafold.com/users/me. If the user lacks credentials for BigQuery, click on + Add credentials, select BigQuery datasource from the list, and click Create credentials:
The user will be redirected to accounts.google.com and then returned to the previous page:
Select BigQuery credentials from the list, input the Temporary Schema field in the format <project>.<datafold_tmp_<username>>, and click Update:
INFOUsers can update BigQuery credentials only if they have the correct permissions for <datafold_tmp_<username>.