


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, you need to set up an API Client in commercetools. Log into your commercetools account and navigate to the "API Clients" section in the Merchant Center. Create a new API client with the necessary permissions to read the data you need, such as "view_products" for product data. Note down the Client ID, Client Secret, and Project Key as you will need these to authenticate API requests.
Ensure you have `Node.js` and `npm` installed on your local machine. These tools will be used to run scripts that interact with the commercetools API. You can download them from [nodejs.org](https://nodejs.org/).
Open your terminal and create a new directory for your project. Navigate into this directory and initialize a new Node.js project by running:
```bash
npm init -y
```
This will create a `package.json` file which will manage your project's dependencies.
Install the commercetools JavaScript SDK to simplify API interactions. Run the following command in your terminal:
```bash
npm install @commercetools/sdk-client @commercetools/api-request-builder
```
These packages will allow you to authenticate and build requests to the commercetools API.
Create a new JavaScript file, e.g., `fetchData.js`. Use the commercetools SDK to authenticate and fetch the required data. Here's a basic template for fetching product data:
```javascript
const { createClient } = require('@commercetools/sdk-client');
const { createAuthMiddlewareForClientCredentialsFlow } = require('@commercetools/sdk-middleware-auth');
const { createHttpMiddleware } = require('@commercetools/sdk-middleware-http');
const { createApiBuilderFromCtpClient } = require('@commercetools/api-request-builder');
const fetch = require('node-fetch');
const projectKey = 'YOUR_PROJECT_KEY';
const clientId = 'YOUR_CLIENT_ID';
const clientSecret = 'YOUR_CLIENT_SECRET';
const client = createClient({
middlewares: [
createAuthMiddlewareForClientCredentialsFlow({
host: 'https://auth.europe-west1.gcp.commercetools.com',
projectKey,
credentials: {
clientId,
clientSecret,
},
fetch,
}),
createHttpMiddleware({
host: 'https://api.europe-west1.gcp.commercetools.com',
fetch,
}),
],
});
const apiRoot = createApiBuilderFromCtpClient(client).withProjectKey({ projectKey });
apiRoot.products().get().execute()
.then(response => {
const products = response.body.results;
console.log(products);
})
.catch(error => console.error(error));
```
Modify the script to save the fetched data into a local JSON file. You can use Node.js's filesystem module to write data to a file:
```javascript
const fs = require('fs');
apiRoot.products().get().execute()
.then(response => {
const products = response.body.results;
fs.writeFileSync('products.json', JSON.stringify(products, null, 2));
console.log('Data saved to products.json');
})
.catch(error => console.error(error));
```
Finally, run your script to fetch data from commercetools and save it to a local JSON file. In your terminal, execute the following command:
```bash
node fetchData.js
```
If the script runs successfully, you will find a `products.json` file in your project directory containing the fetched data.
By following these steps, you will be able to securely and efficiently transfer data from commercetools into a locally stored JSON file 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.
Commercetools is a cloud-based headless commerce platform that provides APIs to power e-commerce sales and similar functions for large businesses. Both the company and platform are called Commercetools. The company is headquartered in Munich, Germany with additional offices in Berlin, Germany; Jena, Germany; Amsterdam, Netherlands; London, England and etc. Through its investor REWE Group, it is associated with the omnichannel order fulfillment software solutions providers fulfillmenttools and the payment transactions provider paymenttools. Its clients include Audi, Bang & Olufsen, Carhartt and Nuts.com.
Commercetools's API provides access to a wide range of data related to e-commerce and retail operations. The following are the categories of data that can be accessed through Commercetools's API:
1. Product data: This includes information about products such as name, description, price, availability, and images.
2. Customer data: This includes information about customers such as name, email address, shipping address, and order history.
3. Order data: This includes information about orders such as order number, customer information, product information, and shipping details.
4. Inventory data: This includes information about inventory levels, stock availability, and stock locations.
5. Payment data: This includes information about payment methods, payment status, and transaction details.
6. Shipping data: This includes information about shipping methods, shipping rates, and delivery status.
7. Tax data: This includes information about tax rates, tax rules, and tax exemptions.
8. Analytics data: This includes information about website traffic, customer behavior, and sales performance.
Overall, Commercetools's API provides access to a comprehensive set of data that can help businesses optimize their e-commerce and retail 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: