Connect Your Database - Bytebase Docs

Only Workspace Admin or Workspace DBA role can configure database instance.

To allow Bytebase to execute operations on behalf the end user, you need to supply Bytebase with the connection info for your database instance.

General

AWS

GCP

Azure

General

Connect to the instance on the same host

If you run Bytebase inside Docker and try to connect to a database instance on the same host, then you need to set host as host.docker.internal.

If you run Bytebase without Docker and try to connect to a database instance on the same host, then you need to set host as 127.0.0.1

Connect to the instance from Bytebase Cloud

To make your Bytebase Cloud instance connect to your databases in your internal network, you need to whitelist the following Bytebase Cloud IPs:

34.27.188.162

SSH tunnel

To protect their databases, some hosting providers block direct remote access. However, they often enable SSH, which allows users to connect to their servers remotely using an SSH client. If you want to connect to a database on one of these servers from Bytebase, you will need to create an SSH tunnel. This will allow you to connect to the database without compromising security.

After filling in the standard database connection information, click SSH Connection > Tunnel + Private Key.
Fill in the SSH connection information. The Private Key is used to authenticate the SSH connection. You can also use a password instead.
Click Test Connection. If the connection is successful, click Create to create this instance.

Extra Connection Parameters

When connecting to a database instance, you may need to specify additional parameters to customize the connection behavior. Bytebase provides a feature that allows users to define extra parameters for the database connection string directly in the UI.

Supported Database Connection Parameters

Below are links to official documentation for configuring connection parameters:

PostgreSQL: Connection Parameters
Oracle (Go-ORA): Go-ORA Connection Options
MySQL (Go SQL Driver): Connection Parameters
Microsoft SQL Server (Go-MSSQL): Connection Options

Common Connection Parameters

Parameter	Description	Example
`sslmode`	SSL connection mode (PostgreSQL)	`require`
`connect_timeout`	Timeout for establishing connections	`10`
`readTimeout`	Read timeout for MySQL and MSSQL connections	`30s`
`max_connections`	Maximum number of connections allowed	`100`

For a full list of supported parameters, refer to the official database documentation links above.

External Secret Manager

By default, Bytebase stores the database credentials in an obfuscated format in its own meta store. You can also instruct Bytebase to retrieve the database credential from an external secret manager.

User tries to access database from Bytebase.
Bytebase calls the external secret manager to exchange the configured key for the database password.
Bytebase retrieves the password and connect the database.

HashiCorp Vault

Bytebase only supports KV v2 engine.

Create the secret in Vault like below:

Secret engine name: secret
Secret path: bytebase
Secret key: DB_PASSWORD
Secret: <<YOUR_PASSOWRD>>

Configure instance to retrieve database password from vault:

Specify the Vault URL.
Specify the Vault auth method.
- For Token, specify the token.
- For AppRole, specify the auth role id and secret id.
Specify the secret engine namesecret, secret path bytebase and secret key DB_PASSWORD.

Custom endpoint

If you have a custom external secret manager, you can supply its API endpoint by enclosing it with the mustache {{ }}, e.g {{http://example.com/secrets/mydbkey}}

Sample request

Usually mydbkey is unique for each database and used for exchanging the password for that database.

curl "http://example.com/secrets/mydbkey"

Expected response

Bytebase expects the following JSON response from the external secret manager. The payload.data is the base64-encoded contents of the database password.

{
  "payload": {
    "data": "xxx"
  }
}

AWS

While creating an RDS or Aurora instance, you can choose to enable IAM authentication.

IAM Authentication

Create IAM policy

Go to IAM > Policies and click Create policy.
Select RDS IAM Authentication for service.
Select connect permission and specific as Resources. Check Any in this account.
Any in this account will mark the resource as arn:aws:rds-db:*:<<your-db-id>>:dbuser:*/*, which contains 3 *:
- 1st *: any regions
- 2nd *: any databases
- 3rd *: any database users
This will allow the RDS connect on behalf of all database users in all databases in your account. If you want to limit the connection to specific databases, please follow this doc.
Name it rds-connect and create this policy.

Create IAM user

Go to IAM > Users can click Create user. Name it rds-connector.
Choose Attach policy directly and select the rds-connect policy. Click Next and then click Create user.
On the user detail page, click Create access key.
Choose Application running outside AWS and click Next.
Then you get the access key and the secret access key.

Use IAM Auth in Bytebase

Start Bytebase with AWS IAM credentials by passing the AWS environment variables:

  docker run --init \
  -e AWS_ACCESS_KEY_ID=<<your-access-key>> \
  -e AWS_SECRET_ACCESS_KEY=<<your-secret-access-key>> \
  -e AWS_REGION=<<your-aws-region>> \
  --name bytebase \
  --publish 8080:8080 --pull always \
  bytebase/bytebase:3.8.0

Go to RDS instance detail page, you’ll find the endpoint and port.

Configure instance connection using AWS RDS IAM, create the bytebase user with AWSAuthenticationPlugin and grant permission.

    CREATE USER bytebase@'%' IDENTIFIED WITH AWSAuthenticationPlugin AS 'RDS';

    ALTER USER 'bytebase'@'%' REQUIRE SSL;

    GRANT ALTER, ALTER ROUTINE, CREATE, CREATE ROUTINE, CREATE VIEW,
    DELETE, DROP, EVENT, EXECUTE, INDEX, INSERT, PROCESS, REFERENCES,
    SELECT, SHOW DATABASES, SHOW VIEW, TRIGGER, UPDATE, USAGE,
    RELOAD, LOCK TABLES, REPLICATION CLIENT, REPLICATION SLAVE
    /*!80000 , SET_USER_ID */ON *.* to bytebase@'%';

Use the instance endpoint, port and the username bytebase to connect the instance.

Secrets Manager

Create an IAM user to access the Secrets Manager

It’s recommended to create a dedicated IAM user for Bytebase to retrieve the secrets. You only need to do this once .

Visit IAM to create a new IAM user. Name it bytebase-external-secret.

Attach SecretsManagerReadWrite permission.

After creating the IAM user, create an Access Key to be used by Bytebase later.

Select Third-party service as the use case.

Optionally set the description tag and in the Retrieve access keys screen, record Access key and Secret access key. They will be passed as environment variables when starting Bytebase.

Create secret

Visit AWS Secrets Manager to store a new secret. Select Other type of secret, and add a key/value pair. The key is DB_PASSWORD and the value is your database user password.

Next to the Configure secret, use bytebase as the Secret name

Skip rotation, review and create the secret.

Use secret in Bytebase

Restart Bytebase with the following environment variables

AWS_REGION=us-east-1
AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are the ones you previously created on the IAM user:

AWS_REGION=us-east-1 AWS_ACCESS_KEY_ID=xxx AWS_SECRET_ACCESS_KEY=yyy ./bytebase <<other options>>

docker run --init \
  -e AWS_REGION=us-east-1 AWS_ACCESS_KEY_ID=xxx AWS_SECRET_ACCESS_KEY=yyy \
  --name bytebase \
  <<other options>>

Go to instance setting, specify bytebase as the Secret name and DB_PASSWORD as the Secret key. These two correspond to the value you created in the AWS Secrets Manager.

GCP

IAM Authentication

Create a service account

Visit Service accounts to create a new service account bytebase.
Grant Cloud SQL Admin permission to the service account.
After the service account is created, you may view the email for the service account bytebase@<<you-project-name>>.iam.gserviceaccount.com. Go to KEYS.
Click ADD KEY and then Create new key.
Choose JSON as the key type and click CREATE. Keep the downloaded private key file. This will be passed as environment variables when starting Bytebase.
Go to Cloud SQL database instance detail page, and make sure cloudsql_iam_authentication is enabled.
Go to Users tab, and click ADD USER ACCOUNT.
Select Cloud IAM and copy/paste the service account email bytebase@<<your-project-name>>.iam.gserviceaccount.com.
Then you can get the Cloud SQL IAM user: bytebase.

Use IAM Auth in Bytebase

Start Bytebase with Google IAM credentials by passing GOOGLE_APPLICATION_CREDENTIALS as an environment variable:

  docker run --init \
  -e GOOGLE_APPLICATION_CREDENTIALS=<<your-json-file>> \
  --name bytebase \
  --publish 8080:8080 --pull always \
  --volume ~/.bytebase/data:/var/opt/bytebase \
  bytebase/bytebase:3.8.0

Go to SQL overview page, you’ll find the Connection name, use it as the host. Choose Google Cloud SQL IAM along with your user bytebase to connect to the database.

Secret Manager

Create a service account to access the Secret Manager

It’s recommended to create a dedicated service account for Bytebase to retrieve the secrets. You only need to do this once .

Visit Service accounts to create a new service account.

Grant Secret Manager Secret Accessor permission to the service account.

After the service account is created, visit its KEYS page and add a new key.

Choose JSON as the key type and create. Keep the downloaded private key file. This will be passed as environment variables when starting Bytebase.

Create secret

Visit GCP Secret Manager to create a new secret.

After creation, note the fully qualified secret name.

Use secret in Bytebase

Restart Bytebase by specifying GOOGLE_APPLICATION_CREDENTIALS=private key file as an environment variable. The private key file is the JSON file downloaded before for the service account.

If you run Bytebase in docker, you need to put the JSON file under the mounted directory. Otherwise, Bytebase won’t be able to access the key file.

docker run --init \
  -e GOOGLE_APPLICATION_CREDENTIALS=/var/opt/bytebase/key.json \
  --name bytebase \
  --volume ~/.bytebase/data:/var/opt/bytebase \
  <<other options>>

Go to instance setting, specify the fully qualified name such as projects/228712144016/secrets/DB_PASSWORD as the Secret full name.

Azure

Entra Managed Identity

Bytebase supports connect to Azure SQL through Azure IAM by using default Azure credential and client secret credential. This section introduces how to use system-assigned managed identity to connect to Azure SQL. For more information about the credential chain in default Azure credential, please refer to default azure credential overview.

Create a VM with enabled system-assigned managed identity

Enable system assigned managed identity while creating a VM.

Deploy the Bytebase on the VM in Docker:

  docker run --init \
  --network=host \
  --name bytebase \
  --pull always \
  --volume ~/.bytebase/data:/var/opt/bytebase \
  bytebase/bytebase:3.8.0

Enable Microsoft Entra Authentication in Azure SQL

Go to the Azure SQL panel, and set the Microsoft Entra Admin for Azure SQL managed instance, don’t forget to click Save button. Once you set the Microsoft Entra Admin, the Microsoft Entra authentication is enabled. Check the Microsoft guide if you use Azure SQL on VM.

Create a contained database user

Connect to the Azure SQL database using the Microsoft Entra Admin account.

For each databases desired to be managed by Bytebase, running the following SQL command inside the database to a contained database user:

   CREATE USER [<Microsoft_Entra_principal_name>] FROM EXTERNAL PROVIDER;
   ALTER ROLE db_owner ADD MEMBER [<Microsoft_Entra_principal_name>];

Connect to Azure SQL Database in Bytebase

Using Azure IAM default credential to connect to Azure SQL database:

In this way, Bytebase can only connect to one specific Azure SQL database. To manage multiple Azure SQL databases in one instance inside Bytebase, considering set the VM principal as the Azure SQL Managed Instance Microsoft Entra Admin.

Database-Specific Configuration

If the connecting instance is managed by the cloud provider, then SUPERUSER is not available and you should create the role via that provider’s admin console. The created role will have provider specific restricted semi-SUPERUSER privileges:

In AWS RDS, the roll is rds_superuser.
In Google Cloud SQL, the role is cloudsqlsuperuser.

You should grant Bytebase privileges with that semi-SUPERUSER role, e.g.:

-- For AWS RDS
GRANT rds_superuser TO bytebase

-- For Google Cloud SQL
GRANT cloudsqlsuperuser TO bytebase

Besides, you may need to grant Bytebase privileges with GRANT role_name TO bytebase; for all existing roles. Otherwise, Bytebase may not access existing databases or tables.

To prevent blocking operations for a long time, consider setting a lock_timeout on the Bytebase user.

In AWS RDS, the roll is rds_superuser.
In Google Cloud SQL, the role is cloudsqlsuperuser.

You should grant Bytebase privileges with that semi-SUPERUSER role, e.g.:

-- For AWS RDS
GRANT rds_superuser TO bytebase

-- For Google Cloud SQL
GRANT cloudsqlsuperuser TO bytebase

Besides, you may need to grant Bytebase privileges with GRANT role_name TO bytebase; for all existing roles. Otherwise, Bytebase may not access existing databases or tables.

To prevent blocking operations for a long time, consider setting a lock_timeout on the Bytebase user.

For managing Oracle database, Bytebase provides two manage modes: Manage based on database and Manage based on schema. You can choose the manage mode when adding an instance or in the instance detail page.

Manage based on database

In this mode, Bytebase will manage the database as a whole.

For normal Oracle instance, we treat the Oracle database as a Bytebase database.
For CDB instance, we treat the CDB and all PDBs as Bytebase databases.
For PDB instance, we treat the PDB as a Bytebase database.

Manage based on schema

In this mode, Bytebase will manage the schema as a whole.

For any Oracle database, we treat the Oracle schema as a Bytebase database.

Go to Atlas MongoDB Security > Network Access and add IP allowing access from Anywhere.

Go to Atlas MongoDB Deployment > Database, and click Connect.

Click Connect to your application.

Find this string cluster0.8bxxxbz.mongodb.net. Go back to Bytebase, put the string into Host or Socket, and leave Port empty.

Choose mongodb+srv:// as Connection String Schema.

To find the Account Locator, go to your Snowflake account, you can find it in the URL, or from the locator field (but lower case).

If the account is located in the AWS US West (Oregon) region, then it would be something like xy12345, otherwise, the format will be <<account_locator>>.<<cloud_region_id>>.<<cloud>> such as xy12345.us-east-2.aws. See official doc.

If you use ClickHouse Cloud. Go to your ClickHouse Cloud account, and click View connection string. Also make sure to whitelist the IP where Bytebase connects from.

In Environment, select your database. Then fill Host or Socket, Warehouse ID and Token.

Host or Socket. Copy it from the URL of your Databricks account.

Warehouse ID. Go to SQL Warehouses and click your warehouse (that is, your database), copy the ID in Overview section.

Token. Go to your avatar on the upper-right of Databricks to find Settings. Click Developer and then Access tokens, where you Generate new token and copy it to paste under Token in Bytebase.

Click Test Connection to verify.

For connecting to Google Cloud Spanner, you need to provide the following info:

Google cloud project ID.
Google cloud Spanner instance ID.
Google cloud service account credentials.

Specify Google Cloud Project ID and Spanner Instance ID

From the Spanner database detail page, you can get the project ID and the instance ID from the URL.

For example, the project ID and instance ID are spanner-test-3717002 and spanner-bb1 respectively for the above database.

Create a Google Cloud Service Account as the Credential

Go to Google Cloud console.
Click APIs & Services and then Credentials. You might have to click Menu on the top left first.
Click Create Credentials and then Service account.
For Service account name, enter a name for the service account.
Click Create and Continue.
For Select a role, select Cloud Spanner Database Admin for the service account.
Click Done.
Click the created service account.
At the top, click Keys and then Add Key and then Create new key. Make sure the key type is set to JSON and click Create.
You’ll get a message that the service account’s private key JSON file was downloaded to your computer. Make a note of the file name and where your browser saves it. You’ll need it later.

Upload the JSON file to the Credentials input.

Introduction

Install

Quick Start

Onboarding Guides

General

AWS

GCP

Azure

​General

​Connect to the instance on the same host

​Connect to the instance from Bytebase Cloud

​SSH tunnel

​Extra Connection Parameters

​External Secret Manager

​HashiCorp Vault

​Custom endpoint

​AWS

​IAM Authentication

​Create IAM policy

​Create IAM user

​Use IAM Auth in Bytebase

​Secrets Manager

​Create an IAM user to access the Secrets Manager

​Create secret

​Use secret in Bytebase

​GCP

​IAM Authentication

​Create a service account

​Use IAM Auth in Bytebase

​Secret Manager

​Create a service account to access the Secret Manager

​Create secret

​Use secret in Bytebase

​Azure

​Entra Managed Identity

​Create a VM with enabled system-assigned managed identity

​Enable Microsoft Entra Authentication in Azure SQL

​Create a contained database user

​Connect to Azure SQL Database in Bytebase

​Database-Specific Configuration

​Manage based on database

​Manage based on schema

​Specify Google Cloud Project ID and Spanner Instance ID

​Create a Google Cloud Service Account as the Credential

General

Connect to the instance on the same host

Connect to the instance from Bytebase Cloud

SSH tunnel

Extra Connection Parameters

External Secret Manager

HashiCorp Vault

Custom endpoint

AWS

IAM Authentication

Create IAM policy

Create IAM user

Use IAM Auth in Bytebase

Secrets Manager

Create an IAM user to access the Secrets Manager

Create secret

Use secret in Bytebase

GCP

IAM Authentication

Create a service account

Use IAM Auth in Bytebase

Secret Manager

Create a service account to access the Secret Manager

Create secret

Use secret in Bytebase

Azure

Entra Managed Identity

Create a VM with enabled system-assigned managed identity

Enable Microsoft Entra Authentication in Azure SQL

Create a contained database user

Connect to Azure SQL Database in Bytebase

Database-Specific Configuration

Manage based on database

Manage based on schema

Specify Google Cloud Project ID and Spanner Instance ID

Create a Google Cloud Service Account as the Credential