How to load data from Google Directory to MySQL Destination

Learn how to use Airbyte to synchronize your Google Directory data into MySQL Destination within minutes.

Try Airbyte Cloud Manual method (the hard way)

Building your pipeline or Using Airbyte

Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.

Building in-house pipelines

Bespoke pipelines are:

Inconsistent and inaccurate data
Laborious and expensive
Brittle and inflexible

Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

After Airbyte

Airbyte connections are:

Reliable and accurate
Extensible and scalable for all your needs
Deployed and governed your way

All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and AI Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Google Directory connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up MySQL Destination for your extracted Google Directory data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Google Directory to MySQL Destination in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Try Airbyte Cloud Manual method (the hard way)

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Talk to our team

Setup Complexities simplified!

You don’t need to put hours into figuring out how to use Airbyte to achieve your Data Engineering goals.

Simple & Easy to use Interface

Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.

Guided Tour: Assisting you in building connections

Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.

Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes

Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.

Try Airbyte Cloud Manual method (the hard way)

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Raman Singh

Tech Lead at Symend

Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

Learn more

Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more

Rupak Patel

Operational Intelligence Manager

"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."

Learn more

How to Sync to Manually

Step 1: Set Up Google Directory API Access

Begin by enabling the Google Directory API for your Google Cloud project. Visit the Google Cloud Console, and ensure you have the necessary permissions to enable APIs and manage service accounts. Create a new project if needed, then navigate to the API Library, search for "Admin SDK," and enable it.

Step 2: Authenticate with OAuth 2.0

Set up OAuth 2.0 credentials in the API & Services Credentials section of your Google Cloud Console. Choose "OAuth client ID" and configure the consent screen. Download the JSON file containing your client ID and client secret. This file will be used for authenticating API requests.

Step 3: Install and Configure Google API Client Library

On your local machine or server, install the Google API Client Library for Python using `pip install --upgrade google-api-python-client`. This library will help in making authorized requests to the Google Directory API. Configure the library using the downloaded JSON credentials to authenticate API requests.

Step 4: Fetch Data from Google Directory

Use the Google API Client Library to fetch user data from the Google Directory. Write a script in Python that authenticates using the credentials and makes an API call to the `users.list` endpoint. This will retrieve information about users within your organization's Google Workspace.

Step 5: Prepare the MySQL Database

Ensure you have a MySQL database ready to store the data. Create a new database and define a table structure that matches the data schema fetched from Google Directory. Use appropriate data types for each column to ensure data integrity.

Step 6: Transform and Clean Data

Process the data retrieved from Google Directory to match the structure of your MySQL table. This could involve transforming JSON data into a format suitable for SQL insertion. Handle any necessary data cleaning, such as dealing with missing values or normalizing data formats.

Step 7: Insert Data into MySQL Database

Connect to your MySQL database using a MySQL client library, such as `mysql-connector-python`. Write a script to iterate over the transformed data and insert each record into the MySQL table. Use prepared statements or parameterized queries to improve security and performance during the insertion process.

By following these steps, you can move data from Google Directory to a MySQL destination without relying on third-party connectors or integrations.