

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.
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes



Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
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
Move Large Volumes, Fast
An Extensible Open-Source Standard
Full Control & Security
Fully Featured & Integrated
Enterprise Support with SLAs
What our users say

Andre Exner

"For TUI Musement, Airbyte cut development time in half and enabled dynamic customer experiences."

Chase Zieman

“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.”

Rupak Patel
"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."
First, create a new project in the Google Cloud Console if you haven't already. Navigate to the Google Cloud Console, select "New Project" from the project dropdown, and follow the prompts to create your project. Ensure that the Pub/Sub API is enabled for this project by searching for "Pub/Sub" in the APIs & Services dashboard and enabling it.
In the Google Cloud Console, navigate to the Pub/Sub section. Click on "Create Topic" and provide a name for your topic. This topic will be the destination for the data coming from Webflow.
Create a service account in your Google Cloud project to interact with Pub/Sub. Go to the "IAM & Admin" section, select "Service Accounts," and click on "Create Service Account." Assign a role with Pub/Sub Publisher permissions. Once created, generate a JSON key for this service account, which will be used in your scripts to authenticate API requests.
In your Webflow project, design a form that captures the data you want to send to Pub/Sub. Ensure that the form fields are named appropriately for capturing the necessary data. Save the form and note down the form ID and site details, as you will need this information for the next steps.
Use the Webflow API to create a webhook that triggers whenever a form submission occurs. You can create this webhook by making a POST request to Webflow's API with the appropriate credentials. The webhook should point to an endpoint you control (e.g., hosted on a server or cloud function), which will handle the incoming data and prepare it for Pub/Sub.
Create a script or a small web application that will receive the data from the Webflow webhook. This can be done using a language like Python, Node.js, or your preferred server-side language. The script should parse the incoming data, authenticate with Google Cloud using the service account JSON key, and publish the data to the designated Pub/Sub topic. Use the Google Cloud Pub/Sub client library for your chosen language to facilitate this.
Submit a test form on your Webflow site to trigger the entire process. Verify that the data is correctly received by your server endpoint and is successfully published to Google Pub/Sub. Use the Google Cloud Console to monitor the Pub/Sub topic and ensure that messages are appearing as expected. Implement logging and error handling in your server script to troubleshoot any issues that arise during this process.
By following these steps, you can transfer data from Webflow to Google Pub/Sub without relying on third-party connectors or integrations.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Webflow is basically a great platform for web designs that can build production-ready experiences without code. Webflow is the leading platform to design, and launch powerful websites visually that enables you to rapidly design and build production-scale responsive websites and it is also an popular platform of CMS, and hosting provider perfect for building production websites and prototypes without coding. Webflow is an overall innovative tool to simplify the lives of designers and teams all around and helping them work faster and deliver high quality websites.
Webflow's API provides access to a wide range of data related to websites built on the Webflow platform. The following are the categories of data that can be accessed through the API:
1. Site data: This includes information about the website, such as its name, URL, and settings.
2. Collection data: This includes data related to collections, such as the name, description, and fields.
3. Item data: This includes data related to individual items within a collection, such as the item's ID, name, and field values.
4. Asset data: This includes data related to assets used on the website, such as images, videos, and files.
5. Form data: This includes data related to forms on the website, such as form submissions and form fields.
6. E-commerce data: This includes data related to e-commerce functionality on the website, such as products, orders, and customers.
7. CMS data: This includes data related to the content management system used on the website, such as templates, pages, and content.
Overall, the Webflow API provides access to a wide range of data that can be used to build custom integrations and applications that interact with Webflow websites.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: