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Fivetran

Incubating

Important Capabilities​

CapabilityStatusNotes
Column-level Lineage✅Enabled by default, can be disabled via configuration include_column_lineage
Detect Deleted Entities✅Optionally enabled via stateful_ingestion.remove_stale_metadata
Platform Instance✅Enabled by default

This plugin extracts fivetran users, connectors, destinations and sync history. This plugin is in beta and has only been tested on Snowflake connector.

Integration Details​

This source extracts the following:

  • Connectors in fivetran as Data Pipelines and Data Jobs to represent data lineage information between source and destination.
  • Connector sources - DataJob input Datasets.
  • Connector destination - DataJob output Datasets.
  • Connector runs - DataProcessInstances as DataJob runs.

Configuration Notes​

  1. Fivetran supports the fivetran platform connector to dump the log events and connectors, destinations, users and roles metadata in your destination.
  2. You need to setup and start the initial sync of the fivetran platform connector before using this source. Refer link.
  3. Once initial sync up of your fivetran platform connector is done, you need to provide the fivetran platform connector's destination platform and its configuration in the recipe.

Concept mapping​

FivetranDatahub
ConnectorDataJob
SourceDataset
DestinationDataset
Connector RunDataProcessInstance

Source and destination are mapped to Dataset as an Input and Output of Connector.

Current limitations​

Works only for Snowflake destination for now.

Snowflake destination Configuration Guide​

  1. If your fivetran platform connector destination is snowflake, you need to provide user details and its role with correct privileges in order to fetch metadata.
  2. Snowflake system admin can follow this guide to create a fivetran_datahub role, assign it the required privileges, and assign it to a user by executing the following Snowflake commands from a user with the ACCOUNTADMIN role or MANAGE GRANTS privilege.
create or replace role fivetran_datahub;

// Grant access to a warehouse to run queries to view metadata
grant operate, usage on warehouse "<your-warehouse>" to role fivetran_datahub;

// Grant access to view database and schema in which your log and metadata tables exist
grant usage on DATABASE "<fivetran-log-database>" to role fivetran_datahub;
grant usage on SCHEMA "<fivetran-log-database>"."<fivetran-log-schema>" to role fivetran_datahub;

// Grant access to execute select query on schema in which your log and metadata tables exist
grant select on all tables in SCHEMA "<fivetran-log-database>"."<fivetran-log-schema>" to role fivetran_datahub;

// Grant the fivetran_datahub to the snowflake user.
grant role fivetran_datahub to user snowflake_user;

Advanced Configurations​

Working with Platform Instances​

If you've multiple instances of source/destination systems that are referred in your fivetran setup, you'd need to configure platform instance for these systems in fivetran recipe to generate correct lineage edges. Refer the document Working with Platform Instances to understand more about this.

While configuration of platform instance for source system you need to provide connector id as key and for destination system provide destination id as key.

Example - Multiple Postgres Source Connectors each reading from different postgres instance​

    # Map of connector source to platform instance
    sources_to_platform_instance:
      postgres_connector_id1: 
        platform_instance: cloud_postgres_instance
        env: PROD

      postgres_connector_id2:
        platform_instance: local_postgres_instance
        env: DEV

Example - Multiple Snowflake Destinations each writing to different snowflake instance​

    # Map of destination to platform instance
    destination_to_platform_instance:
      snowflake_destination_id1: 
        platform_instance: prod_snowflake_instance
        env: PROD

      snowflake_destination_id2:
        platform_instance: dev_snowflake_instance
        env: PROD

CLI based Ingestion​

Install the Plugin​

pip install 'acryl-datahub[fivetran]'

Starter Recipe​

Check out the following recipe to get started with ingestion! See below for full configuration options.

For general pointers on writing and running a recipe, see our main recipe guide.

source:
  type: fivetran
  config:
    # Fivetran log connector destination server configurations
    fivetran_log_config:
      destination_platform: snowflake
      destination_config:
        # Coordinates
        account_id: "abc48144"
        warehouse: "COMPUTE_WH"
        database: "MY_SNOWFLAKE_DB"
        log_schema: "FIVETRAN_LOG"

        # Credentials
        username: "${SNOWFLAKE_USER}"
        password: "${SNOWFLAKE_PASS}"
        role: "snowflake_role"

    # Optional - filter for certain connector names instead of ingesting everything.
    # connector_patterns:
    #   allow:
    #     - connector_name

    # Optional -- A mapping of the connector's all sources to its database.
    # sources_to_database:
    #   connector_id: source_db
    
    # Optional -- This mapping is optional and only required to configure platform-instance for source
    # A mapping of Fivetran connector id to data platform instance
    # sources_to_platform_instance:
    #   connector_id:
    #     platform_instance: cloud_instance
    #     env: DEV

    # Optional -- This mapping is optional and only required to configure platform-instance for destination.
    # A mapping of Fivetran destination id to data platform instance
    # destination_to_platform_instance:
    #   destination_id:
    #     platform_instance: cloud_instance
    #     env: DEV

sink:
  # sink configs

Config Details​

Note that a . is used to denote nested fields in the YAML recipe.

FieldDescription
fivetran_log_config ✅
FivetranLogConfig
Fivetran log connector destination server configurations.
fivetran_log_config.destination_platform
string
The destination platform where fivetran connector log tables are dumped.
Default: snowflake
fivetran_log_config.destination_config
DestinationConfig
If destination platform is 'snowflake', provide snowflake configuration.
fivetran_log_config.destination_config.account_id ❓
string
Snowflake account identifier. e.g. xy12345, xy12345.us-east-2.aws, xy12345.us-central1.gcp, xy12345.central-us.azure, xy12345.us-west-2.privatelink. Refer Account Identifiers for more details.
fivetran_log_config.destination_config.database ❓
string
The fivetran connector log database.
fivetran_log_config.destination_config.log_schema ❓
string
The fivetran connector log schema.
fivetran_log_config.destination_config.authentication_type
string
The type of authenticator to use when connecting to Snowflake. Supports "DEFAULT_AUTHENTICATOR", "OAUTH_AUTHENTICATOR", "EXTERNAL_BROWSER_AUTHENTICATOR" and "KEY_PAIR_AUTHENTICATOR".
Default: DEFAULT_AUTHENTICATOR
fivetran_log_config.destination_config.connect_args
object
Connect args to pass to Snowflake SqlAlchemy driver
fivetran_log_config.destination_config.options
object
Any options specified here will be passed to SQLAlchemy.create_engine as kwargs.
fivetran_log_config.destination_config.password
string(password)
Snowflake password.
fivetran_log_config.destination_config.private_key
string
Private key in a form of '-----BEGIN PRIVATE KEY-----\nprivate-key\n-----END PRIVATE KEY-----\n' if using key pair authentication. Encrypted version of private key will be in a form of '-----BEGIN ENCRYPTED PRIVATE KEY-----\nencrypted-private-key\n-----END ECNCRYPTED PRIVATE KEY-----\n' See: https://docs.snowflake.com/en/user-guide/key-pair-auth.html
fivetran_log_config.destination_config.private_key_password
string(password)
Password for your private key. Required if using key pair authentication with encrypted private key.
fivetran_log_config.destination_config.private_key_path
string
The path to the private key if using key pair authentication. Ignored if private_key is set. See: https://docs.snowflake.com/en/user-guide/key-pair-auth.html
fivetran_log_config.destination_config.role
string
Snowflake role.
fivetran_log_config.destination_config.scheme
string
Default: snowflake
fivetran_log_config.destination_config.username
string
Snowflake username.
fivetran_log_config.destination_config.warehouse
string
Snowflake warehouse.
fivetran_log_config.destination_config.oauth_config
OAuthConfiguration
oauth configuration - https://docs.snowflake.com/en/user-guide/python-connector-example.html#connecting-with-oauth
fivetran_log_config.destination_config.oauth_config.authority_url ❓
string
Authority url of your identity provider
fivetran_log_config.destination_config.oauth_config.client_id ❓
string
client id of your registered application
fivetran_log_config.destination_config.oauth_config.provider ❓
Enum
Identity provider for oauth.Supported providers are microsoft and okta.
fivetran_log_config.destination_config.oauth_config.client_secret
string(password)
client secret of the application if use_certificate = false
fivetran_log_config.destination_config.oauth_config.encoded_oauth_private_key
string
base64 encoded private key content if use_certificate = true
fivetran_log_config.destination_config.oauth_config.encoded_oauth_public_key
string
base64 encoded certificate content if use_certificate = true
fivetran_log_config.destination_config.oauth_config.scopes
array(string)
fivetran_log_config.destination_config.oauth_config.use_certificate
boolean
Do you want to use certificate and private key to authenticate using oauth
Default: False
include_column_lineage
boolean
Populates table->table column lineage.
Default: True
platform_instance
string
The instance of the platform that all assets produced by this recipe belong to
sources_to_database
map(str,string)
env
string
The environment that all assets produced by this connector belong to
Default: PROD
connector_patterns
AllowDenyPattern
Regex patterns for connectors to filter in ingestion.
Default: {'allow': ['.*'], 'deny': [], 'ignoreCase': True}
connector_patterns.allow
array(string)
connector_patterns.deny
array(string)
connector_patterns.ignoreCase
boolean
Whether to ignore case sensitivity during pattern matching.
Default: True
destination_to_platform_instance
map(str,PlatformDetail)
destination_to_platform_instance.key.platform_instance
string
The instance of the platform that all assets produced by this recipe belong to
destination_to_platform_instance.key.env
string
The environment that all assets produced by DataHub platform ingestion source belong to
Default: PROD
sources_to_platform_instance
map(str,PlatformDetail)
sources_to_platform_instance.key.platform_instance
string
The instance of the platform that all assets produced by this recipe belong to
sources_to_platform_instance.key.env
string
The environment that all assets produced by DataHub platform ingestion source belong to
Default: PROD
stateful_ingestion
StatefulStaleMetadataRemovalConfig
Airbyte Stateful Ingestion Config.
stateful_ingestion.enabled
boolean
The type of the ingestion state provider registered with datahub.
Default: False
stateful_ingestion.remove_stale_metadata
boolean
Soft-deletes the entities present in the last successful run but missing in the current run with stateful_ingestion enabled.
Default: True

Code Coordinates​

  • Class Name: datahub.ingestion.source.fivetran.fivetran.FivetranSource
  • Browse on GitHub

Questions

If you've got any questions on configuring ingestion for Fivetran, feel free to ping us on our Slack.