---
schema_version: "1"
id: b51112c915af0b50f94d1770460f225ea9898410927435f140721602ea7e190e
title: Google BigQuery Connector 1.1
collection: mulesoft
version: current
locale: en-us
portal_url: https://docs.salesforce.com/mulesoft/current/en-us/google-bigquery-connector/1.1/index.md
canonical_url: https://docs.mulesoft.com/google-bigquery-connector/1.1/
source_site: docs.mulesoft.com
content_type: documentation
content_hash: adb45fd10f8029fbeed8c930c1d1b9387dd808c994db51d1611cf70b3bae0325
description: MuleSoft Documentation Site
release: "1.1"
latest: false
---
---
product: Google BigQuery Connector
version: 1.1
---

# Google BigQuery Connector 1.1

> For the full documentation index, see: https://docs.mulesoft.com/llms.txt

Anypoint Connector for Google BigQuery (Google BigQuery Connector) syncs data and automates business
processes between Google BigQuery and third-party applications, either on-premises or in the cloud.

For information about compatibility and fixed issues, refer to the Google BigQuery Connector Release
Notes.

## Before You Begin

To use this connector, you must be familiar with:

- The Google BigQuery API

- Anypoint Connectors

- Mule runtime engine (Mule)

- Elements and global elements in a Mule flow

- How to create a Mule app using Anypoint Studio

Before creating an app, you must have:

- Credentials to access the Google BigQuery target resource

- Anypoint Platform

- Anypoint Studio or Anypoint Code Builder

## Common Use Cases For the Connector

These are some common use cases for Google BigQuery Connector:

- Use log and event data collection to analyze problems

- Insert, update, and delete data in Google BigQuery

  You can insert multiple rows by using multi-row `INSERT` statements in your query or job (for
  example, `INSERT INTO table VALUES (1, 'val1'), (2, 'val2')`). The connector passes the SQL to
  BigQuery. There’s no dedicated bulk insert operation, batching, or optimization for large
  datasets.

  `MERGE` isn’t supported. For merge-like behavior, use a `SELECT` followed by conditional `INSERT`
  or `UPDATE` operations in your flow, which is less efficient and not atomic.

- Execute a query in Google BigQuery

For examples of these use cases, refer to
[Google BigQuery Connector Examples](https://docs.mulesoft.com/google-bigquery-connector/1.1/google-bigquery-connector-examples).

## Connection Types

Google BigQuery connections use the following authentication types:

- JWT Connection  
  Uses a token for authentication

- OAuth2 Connection  
  Uses service account authentication

For information about configuring authentication types, refer to
[Configure a Global Element for the Connector](https://docs.mulesoft.com/google-bigquery-connector/1.1/google-bigquery-connector-studio#configure-global-element).

## Next Step

After you complete the prerequisites, you are ready to create an app and configure the connector
using [Anypoint Studio](https://docs.mulesoft.com/google-bigquery-connector/1.1/google-bigquery-connector-studio).

## See Also

- [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors)

- [Use Exchange to Discover Connectors, Templates, and Examples](https://docs.mulesoft.com/connectors/introduction/intro-use-exchange)

- [Google BigQuery Connector Reference](https://docs.mulesoft.com/google-bigquery-connector/1.1/google-bigquery-connector-reference)

- [Salesforce Help](https://help.salesforce.com)