How to load data from Google Directory to S3 Glue

Learn how to use Airbyte to synchronize your Google Directory data into S3 Glue within minutes.

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 S3 Glue 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 S3 Glue 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.

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

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.

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 headshot

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: Export Data from Google Directory

Begin by exporting your data from Google Directory. Use Google Takeout to select the specific data you wish to export. Choose the relevant Google services like Google Contacts, Google Drive, or any other data source available in Google Directory. Ensure the data is exported in a compatible format, such as CSV, JSON, or XML, which AWS services can process.

Once the data export is complete, download the data files to your local machine. Organize the files and ensure they are in a structured format ready for upload. If necessary, clean the data to remove any inconsistencies or errors that might complicate later processing.

Log in to your AWS Management Console and navigate to the S3 service. Create a new S3 bucket or choose an existing one to store your data. Configure the bucket with appropriate permissions to ensure secure access. If you want the data to be accessible to AWS Glue, ensure your IAM roles are properly set up to grant necessary permissions.

Upload the prepared data files to your configured S3 bucket. You can use the AWS Management Console, AWS CLI, or AWS SDKs to perform the upload. Make sure the files are placed in a specified folder or prefix within the bucket for organized access.

In your AWS Management Console, navigate to AWS Glue. Create a new Glue Data Catalog database to store metadata for your dataset. Define a new Glue crawler that will scan your data in S3 and populate the Glue Catalog with table definitions. Configure the crawler's IAM role to ensure it has permission to access the S3 bucket.

Execute the Glue crawler to automatically detect the schema of your data files in the S3 bucket. The crawler will create tables in the Glue Data Catalog, mapping the structure of the data files to Glue tables. Once the crawler completes, verify that the tables are correctly defined and ready for use in data processing tasks.

With your data cataloged, you can now create AWS Glue ETL (Extract, Transform, Load) jobs. Use the Glue Studio or Glue Console to develop scripts that transform and load your data according to your specific requirements. Once your ETL job is configured, run the job to process and move data within AWS infrastructure as needed.

By following these steps, you'll successfully transfer data from Google Directory to AWS S3 Glue using AWS-native tools and features, without relying on third-party connectors or integrations.