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How To Send Data From Your PHP Codebase to Google BigQuery

Google BigQuery is a powerful and scalable data warehouse solution that allows you to analyze large datasets quickly. It is an ideal choice for businesses that need fast and efficient data processing. The great news is that you can seamlessly integrate Google BigQuery with various codebases, including Python, Java, NodeJS, and PHP as well as the Google BigQuery CLI.

In this tutorial, we will guide you through the process of seamlessly sending data from your PHP codebase to Google BigQuery. By integrating BigQuery with PHP, you can tap into the powerful capabilities of BigQuery and unlock valuable insights from your data, regardless of its size. With PHP being a widely adopted web programming language, this integration ensures smooth data transfer, making the entire process easier and more efficient.

Understanding Google BigQuery and PHP integration

In simple terms, Google BigQuery is a cloud-based data warehousing tool that can handle petabyte-scale data. It helps you to store and analyze data using a SQL-like interface in real-time. On the other hand, PHP is a popular server-side scripting language used to create dynamic web pages. Integrating PHP with Google BigQuery opens up new possibilities for real-time data analysis and visualization.

What is Google BigQuery?

Google BigQuery is a SaaS-based, client-ready, enterprise-level data warehouse and analytics platform. This tool allows you to store, transform, and analyze large datasets using SQL-like queries. It offers various security, data sharing, and collaboration features for businesses that rely on data-driven decision-making.

BigQuery is a versatile data processing platform that empowers you to handle a wide range of data types and formats. With BigQuery, you can seamlessly process structured, semi-structured, and unstructured data. It supports popular data formats like CSV, Avro, JSON, and Parquet, allowing you to work with diverse data sources effectively.

BigQuery provides native integration with various data sources, enabling you to process data from multiple origins. You can easily import data from sources like Cloud Storage, stream data in real-time, and integrate with third-party services such as Salesforce and Facebook.

Google BigQuery also provides connectors that allow you to integrate with PostgreSQL, MySQL and other relational databases, enabling data transfer and synchronization between these databases and BigQuery.

It's important to note that while BigQuery can work with PostgreSQL and MySQL, it is not a direct replacement for these databases. BigQuery is primarily designed for analytical workloads and large-scale data processing, whereas PostgreSQL and MySQL are traditional relational databases suited for transactional workloads.

Why use PHP with Google BigQuery?

PHP is a flexible and easy-to-use open-source scripting language that lets you create dynamic web pages and web applications. When combined with Google BigQuery, PHP can parse data in real-time and run complex analytics queries. Whether you want to process e-commerce data, user logs, or IoT sensor data, PHP and Google BigQuery make it easy to handle diverse datasets in a streamlined manner. Plus, it opens up the possibility of integrating with other cloud platforms, such as Google Cloud Storage, Google Analytics, and Google Ads.

Prerequisites for PHP and Google BigQuery integration

You will need a Google Cloud Platform account and a PHP development environment installed on your local machine to integrate PHP with Google BigQuery. This includes a web server (such as Apache or Nginx), PHP (version 5.6 or later), and the necessary extensions required for connecting with Google Cloud SDK and Google BigQuery API. Also, ensure that your PHP environment has access to the Google Cloud SDK (installed on your machine) and that you have created a project in the Google Cloud Console.

Sending data from a PHP application to BigQuery involves building an ETL data pipeline, where you extract data from your app, transform it as needed, and load it into BigQuery for analysis. By integrating PHP with BigQuery, you can streamline your data processing tasks and derive valuable insights.

Setting up your PHP environment

Before you begin, you will need to set up your PHP environment to work with Google BigQuery. This involves installing the necessary extensions and configuring your Google Cloud SDK and API credentials.

Installing PHP and Required Extensions

To install PHP and the required extensions for working with Google BigQuery, follow these steps:

1. Install PHP on your local machine by downloading the binaries from the official PHP website or using a package manager, such as apt-get or yum.

2. Install the Google Cloud PHP Client Library by running the following command. You’ll first need to install the Composer, a dependency manager for PHP, then in your command prompt or terminal, type:

composer require google/cloud-bigquery

3. Ensure that the "google/cloud" library is added to your PHP configuration file (php.ini).

4. Install the "google/auth" library by running the following command:

composer require google/auth

5. Ensure that the "google/auth" library is added to your PHP configuration file (php.ini).

Installing PHP and the required extensions is the first step in setting up your PHP environment for Google BigQuery. These extensions provide the necessary functionality for PHP to communicate with Google BigQuery and perform data analysis tasks.

Configuring Google Cloud CLI

The next step is to configure the Google Cloud CLI on your local machine. Here's how:

Set up a project in the Google Cloud Console:

  1. Go to the Google Cloud Console.
  2. Create a new project or select an existing one.
  3. Enable the BigQuery API for your project.

Google BigQuery gcloud CLI installation

  1. Download and install the Google Cloud CLI.
  2. Run the following command in your command prompt or terminal:
gcloud init

This will prompt you to log in to your Google account and select the project you want to work on.

Enable the BigQuery API by running the command:

gcloud services enable bigquery.googleapis.com

Authenticate your SDK by running the command:

gcloud auth application-default login

This will generate a JSON file with your API credentials.

Configuring the Google Cloud CLI is an important step in setting up your PHP environment for Google BigQuery. The SDK provides the necessary tools and resources for working with Google Cloud Platform services, including BigQuery.

Setting up Google BigQuery API credentials

To connect PHP with Google BigQuery, you need to generate a JSON file with API credentials. Here's how:

  1. Log in to your Google Cloud Console and navigate to the "API & Services" section.
  2. Click on "Credentials" and select "Create Credentials" -> "Service Account Key".
  3. Fill in the required details and select "BigQuery" as the role for this service account.
  4. Click on "Create" to generate a JSON file with your API credentials.

Generating a JSON file with your API credentials is a critical step in setting up your PHP environment for Google BigQuery. This file contains the authentication information necessary for PHP to connect to the BigQuery API and perform data analysis tasks.

Connecting PHP to Google BigQuery

Now that you have set up your PHP environment and generated your API credentials, it's time to connect PHP to Google BigQuery.

To send data from PHP to Google BigQuery, you can use the BigQuery API. Here's a step-by-step guide on how to accomplish this:

Write PHP code to send data to BigQuery:

Be sure to include the necessary classes and initialize the BigQuery client with authentication:

use Google\Cloud\BigQuery\BigQueryClient;
$keyFilePath = '/path/to/your/service-account-key.json';
$projectId = 'your-project-id';
$bigQuery = new BigQueryClient([
'keyFilePath' => $keyFilePath,
'projectId' => $projectId,

Next, define the dataset and table to which you want to send the data:

$datasetId = 'your-dataset-id';
$tableId = 'your-table-id';

Then create a BigQuery table reference:

$dataset = $bigQuery->dataset($datasetId);
$table = $dataset->table($tableId);

Prepare the data to be inserted:

$data = [
['column1' => 'value1', 'column2' => 'value2', ...],
['column1' => 'value3', 'column2' => 'value4', ...],
// Add more rows as needed

Finally, insert the data into the table:


Note: You can also set additional options such as inserting a row ID or skipping invalid rows. Refer to the official documentation for more information.

Run the PHP script:

Now that we have written the PHP script, we’ll run the script to create a connection to BigQuery and start creating the tables that we’ll add data to:

  • Save the PHP script on your server.
  • Run the script using the PHP command-line interface or through a web server.

By following these steps, you should be able to send data from PHP to Google BigQuery using the BigQuery API. Make sure to replace the placeholders ('your-project-id', 'your-dataset-id', 'your-table-id', etc.) with your actual project, dataset, and table details. You can now start to query data!

Note: Before sending your data to BigQuery, you’ll need to prepare it by identifying the relevant data from your PHP app and structuring it according to BigQuery's schema requirements. You can also perform any necessary data transformations or preprocessing using PHP.

Testing the connection

Once you have connected PHP to Google BigQuery, you can test the connection by running a simple query on your BigQuery Data. Here's how:

$query = 'SELECT * FROM `dataset.table` LIMIT 10';
$jobConfig = $client->query($query);
$job = $client->startQuery($jobConfig);

This code snippet queries the "dataset.table" dataset in Google BigQuery and retrieves the first 10 records. If the query runs successfully, and you receive the query results you can be sure that PHP is connected to Google BigQuery.

Working with datasets and tables

Now that you have connected PHP to Google BigQuery and tested the connection, you can start working with datasets and tables. Here's how.

Creating a dataset in Google BigQuery

To create a new dataset in Google BigQuery, use the following code snippet:

$dataset = $bigQuery->createDataset('my_new_dataset');

This code snippet creates a new dataset named "my_new_dataset" in Google BigQuery.

Creating a table and defining schema

To create a new table in Google BigQuery and define its schema, use the following code snippet:

$table = $dataset->createTable('my_new_table', [ 'id' => 'STRING', 'name' => 'STRING', 'age' => 'INTEGER']);

This code snippet creates a new table named "my_new_table" in the previously created dataset and defines its schema with three columns: "id" (string), "name" (string), and "age" (integer).

Managing datasets and tables with PHP

With PHP and Google BigQuery, you can easily manage your datasets and tables. Here are some examples of how to do that.

To list all the datasets in Google BigQuery, use the following code snippet:

$datasets = $bigQuery->listDatasets();
foreach ($datasets as $dataset) {
echo $dataset->name() . PHP_EOL;

To list all the tables in a specific dataset, use the following code snippet:

$tables = $dataset->tables();
foreach ($tables as $table) {
echo $table->name() . PHP_EOL;

To delete a specific table, use the following code snippet:


With these examples, you can easily manage your datasets and tables in Google BigQuery using PHP.

Note: You can reference a library of php operations templates on BigQuery in GCP’s official GitHub doc samples.


With the power of Google's cloud-based SQL tool and PHP's flexibility, you can process, analyze, and visualize large datasets in real-time. In this quickstart tutorial, we explained how you can send data from your PHP codebase to Google BigQuery and manage your datasets and tables using PHP. We hope this guide helps you get started with PHP and Google BigQuery integration and derive insights that drive your business growth forward. Check out RudderStack's PHP Codebase to Google BigQuery integration.

Don't want to go through the pain of direct integration? RudderStack's PHP SDK makes it easy to send data from your PHP app to Google BigQuery.

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