def METHOD_NAME(
    database: str,
    kms_key_id: Optional[str] = None,
    tags: Optional[Dict[str, str]] = None,
    boto3_session: Optional[boto3.Session] = None,
) -> str:
    """Create a new Timestream database.
    Note
    ----
    If the KMS key is not specified, the database will be encrypted with a
    Timestream managed KMS key located in your account.
    Parameters
    ----------
    database: str
        Database name.
    kms_key_id: Optional[str]
        The KMS key for the database. If the KMS key is not specified,
        the database will be encrypted with a Timestream managed KMS key located in your account.
    tags: Optional[Dict[str, str]]
        Key/Value dict to put on the database.
        Tags enable you to categorize databases and/or tables, for example,
        by purpose, owner, or environment.
        e.g. {"foo": "boo", "bar": "xoo"})
    boto3_session : boto3.Session(), optional
        Boto3 Session. The default boto3 Session will be used if boto3_session receive None.
    Returns
    -------
    str
        The Amazon Resource Name that uniquely identifies this database. (ARN)
    Examples
    --------
    Creating a database.
    >>> import awswrangler as wr
    >>> arn = wr.timestream.create_database("MyDatabase")
    """
    _logger.info("Creating Timestream database %s", database)
    client = _utils.client(service_name="timestream-write", session=boto3_session)
    args: Dict[str, Any] = {"DatabaseName": database}
    if kms_key_id is not None:
        args["KmsKeyId"] = kms_key_id
    if tags is not None:
        args["Tags"] = [{"Key": k, "Value": v} for k, v in tags.items()]
    response = client.METHOD_NAME(**args)
    return response["Database"]["Arn"]