Supported Data Sources

Below is a selection of available data sources along with the required and optional connection parameters.

Amazon DynamoDB

Connect Amazon DynamoDB providing the following connection parameters:

dynamodb_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='dynamodb',
    connection_data={
        'aws_access_key_id': 'ASIAW...XGTQ5',
        'aws_secret_access_key': 'oOo2KYKAjd/jbu...AUAbx',
        'aws_session_token': 'IQoJb3...xwaNwvQ=',
        'region_name': 'us-east-2'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

aws_access_key_id: The AWS access key that identifies the user or IAM role.
aws_secret_access_key: The AWS secret access key that identifies the user or IAM role.
region_name: The AWS region to connect to.

Optional connection parameters include the following:

aws_session_token: The AWS session token that identifies the user or IAM role. This becomes necessary when using temporary security credentials.

Amazon Redshift

Connect Amazon Redshift providing the following connection parameters:

redshift_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='redshift',
    connection_data={
        'host': 'samples.mindsdb.com',
        'port': 5439,
        'database': 'sample',
        'user': 'admin',
        'password': 'rXYZ92zXabcfdBXhMnrj6GTXYvcs8XXz'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

host: The host name or IP address of the Redshift cluster.
port: The port to use when connecting with the Redshift cluster.
database: The database name to use when connecting with the Redshift cluster.
user: The username to authenticate the user with the Redshift cluster.
password: The password to authenticate the user with the Redshift cluster.

Optional connection parameters include the following:

schema: The database schema to use. Defaults to public.
sslmode: The SSL mode for the connection.

Amazon S3

Connect Amazon S3 providing the following connection parameters:

s3_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='s3',
    connection_data={
        'aws_access_key_id': 'ASIAW...XGTQ5',
        'aws_secret_access_key': 'oOo2KYKAjd/jbu...AUAbx',
        'aws_session_token': 'IQoJb3...xwaNwvQ=',
        'bucket': 'my-bucket'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

In the context of Amazon S3, the tables refer to the files available in the connected bucket(s). This can be a list of file names or file paths. For example, tables=['file1.csv', 'folder/file2.csv']. Additionally, a special table called files is available that lists all the files along with their content in the connected bucket(s).

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

aws_access_key_id: The AWS access key that identifies the user or IAM role.
aws_secret_access_key: The AWS secret access key that identifies the user or IAM role.

Optional connection parameters include the following:

aws_session_token: The AWS session token that identifies the user or IAM role. This becomes necessary when using temporary security credentials.
bucket: The name of the Amazon S3 bucket. If not provided, all available buckets can be queried, however, this can affect performance, especially when listing all of the available objects.

ClickHouse

Connect ClickHouse providing the following connection parameters:

clickhouse_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='clickhouse',
    connection_data={
        'user': 'default',
        'password': '3ZgXtMqAGxyzp4ZYuRndiXY8tXurptTx',
        'host': 'samples.mindsdb.com',
        'port': 8123,
        'database': 'default',
        'protocol': 'http'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

host: The hostname or IP address of the ClickHouse server.
port: The TCP/IP port of the ClickHouse server.
user: The username used to authenticate with the ClickHouse server.
password: The password to authenticate the user with the ClickHouse server.
database: The database name to use when connecting with the ClickHouse server. Defaults to default.

Optional connection parameters include the following:

protocol: It is an optional parameter. Its supported values are native, http and https. Defaults to native.

Databricks

Connect Databricks providing the following connection parameters:

databricks_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='databricks',
    connection_data={
        'server_hostname': 'xyz-24x23abc-46x7.cloud.databricks.com',
        'http_path': '/sql/1.0/warehouses/123zx7f456e789a7',
        'access_token': 'dxyz9fa1234b6b12b1xyzc2e12345ebc9876',
        'catalog': 'mindsdb',
        'schema': 'default'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

server_hostname: The server hostname for the cluster or SQL warehouse.
http_path: The HTTP path of the cluster or SQL warehouse.
access_token: A Databricks personal access token for the workspace.

Refer to the instructions [1] and [2] to find the connection parameters mentioned above for your compute resource.

Optional connection parameters include the following:

session_configuration: Additional (key, value) pairs to set as Spark session configuration parameters. This should be provided as a JSON string.
http_headers: Additional (key, value) pairs to set in HTTP headers on every RPC request the client makes. This should be provided as a JSON string.
catalog: The catalog to use for the connection.
schema: The schema (database) to use for the connection.

Elasticsearch

Connect Elasticsearch providing the following connection parameters:

elasticsearch_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='elasticsearch',
    connection_data={
        'cloud_id': 'a12345b...gxM2IwMDY4ZDM0',
        'hosts': 'https://1234x419719b45479d4821c1234f8804.us-central1.gcp.cloud.es.io:443',
        'api_key': 'ckXYZ2x...X3haZUhuZx==',
        'user': 'elastic',
        'password': 'XYi0XYoZxLhrXmwXYZt12M7g'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

The connection parameters include the following:

cloud_id: The Cloud ID provided with the ElasticSearch deployment. Required only when hosts is not provided.
hosts: The ElasticSearch endpoint provided with the ElasticSearch deployment. Required only when cloud_id is not provided.
api_key: The API key that you generated for the ElasticSearch deployment. Required only when user and password are not provided.
user and password: The user and password used to authenticate. Required only when api_key is not provided.

Google BigQuery

Connect Google BigQuery providing the following connection parameters:

bigquery_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='bigquery',
    connection_data={
        'project_id': 'my-project-12345',
        'dataset': 'my_dataset',
        'service_account_json': {
                'type': 'service_account',
                'project_id': 'my-project-12345',
                'private_key_id': '03b20...364e609d1',
                'private_key': '-----BEGIN PRIVATE KEY-----\xyz\n-----END PRIVATE KEY-----\n',
                'client_email': 'mindsdb-app@expanded-pride-394015.iam.gserviceaccount.com',
                'client_id': '1234...8123',
                'auth_uri': 'https://accounts.google.com/o/oauth2/auth',
                'token_uri': 'https://oauth2.googleapis.com/token',
                'auth_provider_x509_cert_url': 'https://www.googleapis.com/oauth2/v1/certs',
                'client_x509_cert_url': 'https://www.googleapis.com/robot/v1/metadata/x509/mindsdb-app%40expanded-pride-394015.iam.gserviceaccount.com',
                'universe_domain': 'googleapis.com'
            }
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

project_id: The globally unique identifier for your project in Google Cloud where BigQuery is located.
dataset: The default dataset to connect to.
service_account_json: It stores the content of the service account keys file used to autheticate the user.

MariaDB

Connect MariaDB providing the following connection parameters:

mariadb_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='mariadb',
    connection_data={
        'user': 'user',
        'password': 'password',
        'host': 'samples.mindsdb.com',
        'port': 3307,
        'database': 'test_data'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

user: The username for the MariaDB database.
password: The password for the MariaDB database.
host: The hostname, IP address, or URL of the MariaDB server.
port: The port number for connecting to the MariaDB server.
database: The name of the MariaDB database to connect to.

Alternatively, you can define the url parameter to specify a connection to MariaDB Server using a URI-like string. You can also use mysql:// as the protocol prefix.

Microsoft OneDrive

Before establishing a connection to Microsoft OneDrive, a few prerequisites steps are required:

Navigate to the Azure Portal and sign in with your Microsoft account.
Locate the Microsoft Entra ID service and click on it.
Click on App registrations and then click on New registration.
Enter a name for your application and select the Accounts in this organizational directory only option for the Supported account types field.
Keep the Redirect URI field empty and click on Register.
Click on API permissions and then click on Add a permission.
Select Microsoft Graph and then click on Delegated permissions.
Search for the Files.Read permission and select it.
Click on Add permissions.
Request an administrator to grant consent for the above permissions. If you are the administrator, click on Grant admin consent for [your organization] and then click on Yes.
Copy the Application (client) ID and record it as the client_id parameter, and copy the Directory (tenant) ID and record it as the tenant_id parameter.
Click on Certificates & secrets and then click on New client secret.
Enter a description for your client secret and select an expiration period.
Click on Add and copy the generated client secret and record it as the client_secret parameter.
Click on Authentication and then click on Add a platform.
Select Web and enter https://mdb.ai/verify-auth in the Redirect URIs field.

Now, connect Microsoft OneDrive providing the following connection parameters:

ms_onedrive_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='one_drive',
    connection_data={
        'client_id': '12345678-90ab-cdef-1234-567890abcdef',
        'client_secret': 'abcd1234efgh5678ijkl9012mnop3456qrst7890uvwx',
        'tenant_id': 'abcdef12-3456-7890-abcd-ef1234567890'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

In the context of Microsoft OneDrive, the tables refer to the files available in the connected account. This can be a list of file names or file paths. For example, tables=['file1.csv', 'folder/file2.csv']. Additionally, a special table called files is available that lists all the files along with their content in the connected account.

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

client_id: The client ID of the registered application.
client_secret: The client secret of the registered application.
tenant_id: The tenant ID of the registered application.

Microsoft SQL Server

Connect Microsoft SQL Server providing the following connection parameters:

mssql_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='mssql',
    connection_data={
        'host': 'samples.mindsdb.com',
        'port': 1433,
        'user': 'sa',
        'password': '#eXY1RbcUkJXyy_L',
        'database': 'master'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

user: The username for the Microsoft SQL Server.
password: The password for the Microsoft SQL Server.
host The hostname, IP address, or URL of the Microsoft SQL Server.
database The name of the Microsoft SQL Server database to connect to.

Optional connection parameters include the following:

port: The port number for connecting to the Microsoft SQL Server. Defaults to 1433.
server: The server name to connect to. Typically only used with named instances or Azure SQL Database.

MongoDB

Connect MongoDB providing the following connection parameters:

mongodb_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='mongodb',
    connection_data={
        'host': 'mongodb+srv://user:password@demo-data-mdb.trzfwvb.mongodb.net/',
        'database': 'public'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Use the following parameters to establish the connection:

host: The connection string of the MongoDB server that includes user (user), password (password), host and port (demo-data-mdb.trzfwvb.mongodb.net).
database: The name of the database.

Alternatively, the following set of connection parameters can be used:

username: The username associated with the database.
password: The password to authenticate your access.
host: The host of the MongoDB server.
port: The port through which TCP/IP connection is to be made.
database: The database name to be connected.

MySQL

Connect MySQL providing the following connection parameters:

mysql_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='mysql',
    connection_data={
        'user': 'user',
        'password': 'MindsXYZ123',
        'host': 'samples.mindsdb.com',
        'port': 3306,
        'database': 'public'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

user: The username for the MySQL database.
password: The password for the MySQL database.
host: The hostname, IP address, or URL of the MySQL server.
port: The port number for connecting to the MySQL server.
database: The name of the MySQL database to connect to.

Alternatively, you can define the url parameter to specify a connection to MySQL Server using a URI-like string.

PostgreSQL

Connect PostgreSQL providing the following connection parameters:

postgres_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='postgres',
    connection_data={
        'user': 'demo_user',
        'password': 'demo_password',
        'host': 'samples.mindsdb.com',
        'port': 5432,
        'database': 'demo',
        'schema': 'demo_data'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that the above connection parameters connect to the sample database provided by MindsDB.

Required connection parameters include the following:

user: The username for the PostgreSQL database.
password: The password for the PostgreSQL database.
host: The hostname, IP address, or URL of the PostgreSQL server.
port: The port number for connecting to the PostgreSQL server.
database: The name of the PostgreSQL database to connect to.

Optional connection parameters include the following:

schema: The database schema to use. Defaults to public.
sslmode: The SSL mode for the connection.

Snowflake

Connect Snowflake providing the following connection parameters:

snowflake_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='snowflake',
    connection_data={
        'account': 'abcxyzw-yz12345',
        'user': 'USER',
        'password': 'x1Y2z3f3i4r',
        'database': 'SNOWFLAKE_SAMPLE_DATA',
        'schema': 'SAMPLES'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

account: The Snowflake account identifier. This guide will help you find your account identifier.
user: The username for the Snowflake account.
password: The password for the Snowflake account.
database: The name of the Snowflake database to connect to.

Optional connection parameters include the following:

warehouse: The Snowflake warehouse to use for running queries.
schema: The database schema to use within the Snowflake database. Defaults to PUBLIC.
role: The Snowflake role to use.

Teradata

Connect Teradata providing the following connection parameters:

teradata_config = DatabaseConfig(
    name='datasource_name',
    description='<DESCRIPTION-OF-YOUR-DATA>',
    engine='teradata',
    connection_data={
        'host': '192.168.0.41',
        'user': 'USER',
        'password': 'x1Y2z3f3i4r',
        'database': 'sample_db'
    },
    # Optionally, you can provide the list of tables to be accessed by the Mind. If not provided, the Mind accesses all available tables.
    tables=['<TABLE-1>', '<TABLE-2>', ...]
)

Note that sample parameter values are provided here for reference, and you should replace them with your connection parameters.

Required connection parameters include the following:

host: The hostname, IP address, or URL of the Teradata server.
user: The username for the Teradata database.
password: The password for the Teradata database.

Optional connection parameters include the following:

database: The name of the Teradata database to connect to. Defaults to the user’s default database.

Get Started

Resources

Supported Data Sources

Amazon DynamoDB

Amazon Redshift

Amazon S3

ClickHouse

Databricks

Elasticsearch

Google BigQuery

MariaDB

Microsoft OneDrive

Microsoft SQL Server

MongoDB

MySQL

PostgreSQL

Snowflake

Teradata

Get Started

Resources

​Amazon DynamoDB

​Amazon Redshift

​Amazon S3

​ClickHouse

​Databricks

​Elasticsearch

​Google BigQuery

​MariaDB

​Microsoft OneDrive

​Microsoft SQL Server

​MongoDB

​MySQL

​PostgreSQL

​Snowflake

​Teradata

Amazon DynamoDB

Amazon Redshift

Amazon S3

ClickHouse

Databricks

Elasticsearch

Google BigQuery

MariaDB

Microsoft OneDrive

Microsoft SQL Server

MongoDB

MySQL

PostgreSQL

Snowflake

Teradata