---
title: Google BigQuery
description: Query, list, and insert data in Google BigQuery
---

import { BlockInfoCard } from "@/components/ui/block-info-card"

<BlockInfoCard 
  type="google_bigquery"
  color="#FFFFFF"
/>

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[Google BigQuery](https://cloud.google.com/bigquery) is Google Cloud's fully managed, serverless data warehouse designed for large-scale data analytics. BigQuery lets you run fast SQL queries on massive datasets, making it ideal for business intelligence, data exploration, and machine learning pipelines.

With the Google BigQuery integration in Sim, you can:

- **Run SQL queries**: Execute queries against your BigQuery datasets and retrieve results for analysis or downstream processing
- **List datasets**: Browse available datasets within a Google Cloud project
- **List and inspect tables**: Enumerate tables within a dataset and retrieve detailed schema information
- **Insert rows**: Stream new rows into BigQuery tables for real-time data ingestion

In Sim, the Google BigQuery integration enables your agents to query datasets, inspect schemas, and insert rows as part of automated workflows. This is ideal for automated reporting, data pipeline orchestration, real-time data ingestion, and analytics-driven decision making.
{/* MANUAL-CONTENT-END */}


## Usage Instructions

Connect to Google BigQuery to run SQL queries, list datasets and tables, get table metadata, and insert rows.



## Actions

### `google_bigquery_query`

Run a SQL query against Google BigQuery and return the results

#### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `projectId` | string | Yes | Google Cloud project ID |
| `query` | string | Yes | SQL query to execute |
| `useLegacySql` | boolean | No | Whether to use legacy SQL syntax \(default: false\) |
| `maxResults` | number | No | Maximum number of rows to return |
| `defaultDatasetId` | string | No | Default dataset for unqualified table names |
| `location` | string | No | Processing location \(e.g., "US", "EU"\) |

#### Output

| Parameter | Type | Description |
| --------- | ---- | ----------- |
| `columns` | array | Array of column names from the query result |
| `rows` | array | Array of row objects keyed by column name |
| `totalRows` | string | Total number of rows in the complete result set |
| `jobComplete` | boolean | Whether the query completed within the timeout |
| `totalBytesProcessed` | string | Total bytes processed by the query |
| `cacheHit` | boolean | Whether the query result was served from cache |
| `jobReference` | object | Job reference \(useful when jobComplete is false\) |
|   ↳ `projectId` | string | Project ID containing the job |
|   ↳ `jobId` | string | Unique job identifier |
|   ↳ `location` | string | Geographic location of the job |
| `pageToken` | string | Token for fetching additional result pages |

### `google_bigquery_list_datasets`

List all datasets in a Google BigQuery project

#### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `projectId` | string | Yes | Google Cloud project ID |
| `maxResults` | number | No | Maximum number of datasets to return |
| `pageToken` | string | No | Token for pagination |

#### Output

| Parameter | Type | Description |
| --------- | ---- | ----------- |
| `datasets` | array | Array of dataset objects |
|   ↳ `datasetId` | string | Unique dataset identifier |
|   ↳ `projectId` | string | Project ID containing this dataset |
|   ↳ `friendlyName` | string | Descriptive name for the dataset |
|   ↳ `location` | string | Geographic location where the data resides |
| `nextPageToken` | string | Token for fetching next page of results |

### `google_bigquery_list_tables`

List all tables in a Google BigQuery dataset

#### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `projectId` | string | Yes | Google Cloud project ID |
| `datasetId` | string | Yes | BigQuery dataset ID |
| `maxResults` | number | No | Maximum number of tables to return |
| `pageToken` | string | No | Token for pagination |

#### Output

| Parameter | Type | Description |
| --------- | ---- | ----------- |
| `tables` | array | Array of table objects |
|   ↳ `tableId` | string | Table identifier |
|   ↳ `datasetId` | string | Dataset ID containing this table |
|   ↳ `projectId` | string | Project ID containing this table |
|   ↳ `type` | string | Table type \(TABLE, VIEW, EXTERNAL, etc.\) |
|   ↳ `friendlyName` | string | User-friendly name for the table |
|   ↳ `creationTime` | string | Time when created, in milliseconds since epoch |
| `totalItems` | number | Total number of tables in the dataset |
| `nextPageToken` | string | Token for fetching next page of results |

### `google_bigquery_get_table`

Get metadata and schema for a Google BigQuery table

#### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `projectId` | string | Yes | Google Cloud project ID |
| `datasetId` | string | Yes | BigQuery dataset ID |
| `tableId` | string | Yes | BigQuery table ID |

#### Output

| Parameter | Type | Description |
| --------- | ---- | ----------- |
| `tableId` | string | Table ID |
| `datasetId` | string | Dataset ID |
| `projectId` | string | Project ID |
| `type` | string | Table type \(TABLE, VIEW, SNAPSHOT, MATERIALIZED_VIEW, EXTERNAL\) |
| `description` | string | Table description |
| `numRows` | string | Total number of rows |
| `numBytes` | string | Total size in bytes, excluding data in streaming buffer |
| `schema` | array | Array of column definitions |
|   ↳ `name` | string | Column name |
|   ↳ `type` | string | Data type \(STRING, INTEGER, FLOAT, BOOLEAN, TIMESTAMP, RECORD, etc.\) |
|   ↳ `mode` | string | Column mode \(NULLABLE, REQUIRED, or REPEATED\) |
|   ↳ `description` | string | Column description |
| `creationTime` | string | Table creation time \(milliseconds since epoch\) |
| `lastModifiedTime` | string | Last modification time \(milliseconds since epoch\) |
| `location` | string | Geographic location where the table resides |

### `google_bigquery_insert_rows`

Insert rows into a Google BigQuery table using streaming insert

#### Input

| Parameter | Type | Required | Description |
| --------- | ---- | -------- | ----------- |
| `projectId` | string | Yes | Google Cloud project ID |
| `datasetId` | string | Yes | BigQuery dataset ID |
| `tableId` | string | Yes | BigQuery table ID |
| `rows` | string | Yes | JSON array of row objects to insert |
| `skipInvalidRows` | boolean | No | Whether to insert valid rows even if some are invalid |
| `ignoreUnknownValues` | boolean | No | Whether to ignore columns not in the table schema |

#### Output

| Parameter | Type | Description |
| --------- | ---- | ----------- |
| `insertedRows` | number | Number of rows successfully inserted |
| `errors` | array | Array of per-row insertion errors \(empty if all succeeded\) |
|   ↳ `index` | number | Zero-based index of the row that failed |
|   ↳ `errors` | array | Error details for this row |
|     ↳ `reason` | string | Short error code summarizing the error |
|     ↳ `location` | string | Where the error occurred |
|     ↳ `message` | string | Human-readable error description |


