Google BigQuery

target-bigquery from adswerve

BigQuery loader

The target-bigquery loader sends data into Google BigQuery after it was pulled from a source using an extractor

Available Variants

Getting Started


If you haven't already, follow the initial steps of the Getting Started guide:

  1. Install Meltano
  2. Create your Meltano project

Installation and configuration

  1. Add the target-bigquery loader to your project using
    meltano add
  2. meltano add loader target-bigquery
  3. Configure the target-bigquery settings using
    meltano config
  4. meltano config target-bigquery set --interactive

Next steps

If you run into any issues, learn how to get help.


This plugin currently has no capabilities defined. If you know the capabilities required by this plugin, please contribute!


The target-bigquery settings that are known to Meltano are documented below. To quickly find the setting you're looking for, click on any setting name from the list:

You can override these settings or specify additional ones in your meltano.yml by adding the settings key.

Please consider adding any settings you have defined locally to this definition on MeltanoHub by making a pull request to the YAML file that defines the settings for this plugin.

Project ID (project_id)

  • Environment variable: TARGET_BIGQUERY_PROJECT_ID

BigQuery project

Dataset ID (dataset_id)

  • Environment variable: TARGET_BIGQUERY_DATASET_ID

BigQuery dataset.

The default value will expand to the value of the load_schema extra for the extractor used in the pipeline, which defaults to the extractor's namespace, e.g. tap_gitlab for tap-gitlab.

Location (location)

  • Environment variable: TARGET_BIGQUERY_LOCATION
  • Default Value: US

Credentials Path (credentials_path)

  • Default Value: $MELTANO_PROJECT_ROOT/client_secrets.json

Fully qualified path to client_secrets.json for your service account.

See the "Activate the Google BigQuery API" section of the repository's README and

By default, this file is expected to be at the root of your project directory.

Validate Records (validate_records)

  • Default Value: false
[No description provided.]

Add Metadata Columns (add_metadata_columns)

  • Default Value: false

Add _time_extracted and _time_loaded metadata columns

Replication Method (replication_method)

  • Default Value: append

The Replication method can be:

append: Adding new rows to the table (Default value) truncate: Deleting all previous rows and uploading the new ones to the table incremental: Upserting new rows into the table, using the primary key given by the tap connector (if it finds an old row with same key, updates it. Otherwise it inserts the new row)

WARNING: It is not recommended to use the incremental option (which uses MERGE SQL statement). It might result in loss of production data, because historical records get updated. Instead, we recommend using the append replication method, which will preserve historical data.

Table Prefix (table_prefix)

  • Environment variable: TARGET_BIGQUERY_TABLE_PREFIX

Add prefix to table name

Table Suffix (table_suffix)

  • Environment variable: TARGET_BIGQUERY_TABLE_SUFFIX

Add suffix to table name

Max Cache (max_cache)

  • Environment variable: TARGET_BIGQUERY_MAX_CACHE
  • Default Value: 50

Maximum cache size in MB

Merge State Messages (merge_state_messages)

  • Default Value: false

Whether to merge multiple state messages from the tap into the state file or uses the last state message as the state file. Note that it is not recommended to set this to true when using with Meltano as the merge behavior conflicts with Meltano’s merge process.

Table Config (table_config)

  • Environment variable: TARGET_BIGQUERY_TABLE_CONFIG

A path to a file containing the definition of partitioning and clustering.

Something missing?

This page is generated from a YAML file that you can contribute changes to.

Edit it on GitHub!

Looking for help?

If you're having trouble getting the target-bigquery loader to work, look for an existing issue in its repository, file a new issue, or join the Meltano Slack community and ask for help in the


meltano add loader target-bigquery

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