

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."
Begin by creating a new project in the Google Cloud Console. This will provide you with a controlled environment to manage resources like Pub/Sub. Once the project is created, enable the Pub/Sub API to allow your project to use the service.
In the Google Cloud Console, navigate to the Pub/Sub section and create a new topic. A topic is a named resource to which messages are sent by publishers. Take note of the topic name, as you will use it later to publish messages.
Develop a web server to handle incoming requests from Stripe. You can use a service like Google Cloud Functions or host your server on a compute instance. The server should expose an HTTPS endpoint that Stripe can call when an event occurs. Ensure that this endpoint can parse incoming JSON payloads.
Within your web server code, implement logic to handle Stripe webhooks. This involves verifying the webhook signature to ensure that the request is genuinely from Stripe, and then processing the event payload. Stripe provides libraries in multiple languages to facilitate verification and parsing.
Set up authentication so that your server can interact with Google Cloud services. For security, use a service account with the necessary Pub/Sub Publisher role. Download the service account key file (JSON) and configure your server to authenticate using this key file.
After processing the Stripe webhook event, use Google Pub/Sub client libraries to publish the event data to your Pub/Sub topic. You will use the topic name from step 2 and the authenticated client from step 5. Ensure that the data is correctly formatted as a message for Pub/Sub.
Conduct a thorough test of the entire setup to ensure reliability and correctness. Trigger various events in your Stripe account and verify that they are correctly received by your web server, authenticated, and then published to your Pub/Sub topic. Monitor Google Cloud Pub/Sub for incoming messages to confirm successful data transfer.
By following these steps, you can efficiently move data from Stripe to Google Pub/Sub using native tools and APIs provided by both platforms, ensuring a secure and scalable solution.
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.
Stripe is a technology company focused on helping businesses of all sizes accept web and mobile payments. Stripe software is intended to build a solid economic infrastructure for the internet at global scale. Well-known companies like Salesforce and Facebook accept online payments through Stripe software. Stripe’s innovative applications combined with their solid economic infrastructure support modern business models like crowdfunding and marketplaces. Stripe continues to innovate, partnering with tech-dominant enterprises such as Apple, Google, and Facebook to launch new capabilities.
Stripe's API provides access to a wide range of data related to payment processing and management. The following are the categories of data that can be accessed through Stripe's API:
1. Payment data: This includes information about payments made through Stripe, such as the amount, currency, and status of the payment.
2. Customer data: This includes information about customers who have made payments through Stripe, such as their name, email address, and payment history.
3. Subscription data: This includes information about subscriptions made through Stripe, such as the subscription plan, billing cycle, and status of the subscription.
4. Dispute data: This includes information about disputes raised by customers, such as the reason for the dispute and the status of the dispute resolution process.
5. Balance data: This includes information about the balance of the Stripe account, such as the available balance, pending balance, and currency.
6. Transfer data: This includes information about transfers made from the Stripe account to a bank account, such as the amount, currency, and status of the transfer.
7. Refund data: This includes information about refunds made through Stripe, such as the amount, currency, and status of the refund.
Overall, Stripe's API provides access to a comprehensive set of data related to payment processing and management, enabling businesses to effectively manage their payment operations.
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: