

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."
To begin, sign up for a Pexels account and navigate to the Pexels API section. Here, you'll need to create a new API key. This key will be required to authenticate your requests to the API. Make sure to store this key securely.
Open your Google Sheet and navigate to the Extensions menu. Select "Apps Script"� to open the Google Apps Script editor. This built-in script editor will allow you to write custom JavaScript code to fetch data from the Pexels API and insert it into your Google Sheet.
In the Google Apps Script editor, write a JavaScript function to make an HTTP GET request to the Pexels API. Use the `UrlFetchApp.fetch()` method to perform this request. Ensure you include your API key in the request headers for authentication. Parse the JSON response to extract the necessary data fields you want to add to your Google Sheet.
Example code snippet:
```javascript
function fetchPexelsData() {
const apiKey = 'YOUR_PEXELS_API_KEY';
const url = 'https://api.pexels.com/v1/curated?per_page=10';
const headers = {
"Authorization": apiKey
};
const response = UrlFetchApp.fetch(url, {headers: headers});
const data = JSON.parse(response.getContentText());
return data.photos; // Adjust this line based on your data needs
}
```
In your Google Sheet, create headers in the first row to match the data fields you plan to import from Pexels. For example, if you're importing photo URLs and photographer names, create headers like "Photo URL" and "Photographer Name".
Extend your Apps Script to include a function that writes the fetched data into your Google Sheet. Loop through the data array returned by the Pexels API, and use `sheet.getRange().setValue()` or `sheet.getRange().setValues()` to populate the cells accordingly.
Example insertion code:
```javascript
function insertDataIntoSheet() {
const sheet = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet();
const photos = fetchPexelsData();
photos.forEach((photo, index) => {
sheet.getRange(index + 2, 1).setValue(photo.url); // Photo URL
sheet.getRange(index + 2, 2).setValue(photo.photographer); // Photographer Name
});
}
```
To keep your data up-to-date, set a trigger to run your data-fetching script at regular intervals. In the Apps Script editor, go to the Triggers section and create a new trigger for your script. Set it to run daily, hourly, or at any preferred interval.
Before relying on your script for regular data updates, test it thoroughly. Run the script manually in the Apps Script editor to ensure it fetches and inserts data as expected. Check the console logs for any errors and adjust your code accordingly. Once satisfied, let the automated triggers handle data updates.
By following these steps, you can effectively transfer data from the Pexels API to Google Sheets without third-party tools, ensuring a direct and customized solution for your needs.
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.
The Pexels API enables programmatic access to the entire Pexels content library, including photos, videos. All content is free, and you're welcome to use Pexels content for anything, as long as it stays within our guidelines.The Pexels API is a RESTful JSON API, and you can interact with it from any language or framework with an HTTP library. Alternatively, Pexels maintains some official client libraries that you can use.
Pexels API provides access to a vast collection of high-quality images and videos that can be used for various purposes. The API offers a range of data categories, including:
- Images: Pexels API provides access to millions of high-quality images that can be used for commercial and personal projects. The images are available in various resolutions and formats, including JPEG and PNG.
- Videos: The API also offers access to a large collection of high-quality videos that can be used for commercial and personal projects. The videos are available in various resolutions and formats, including MP4 and MOV.
- Search: Pexels API allows users to search for images and videos based on keywords, categories, and other parameters. The search results can be filtered by various criteria, such as orientation, size, and color.
- Popular: The API provides access to a list of popular images and videos that are currently trending on the platform.
- Curated Collections: Pexels API offers access to a range of curated collections of images and videos that are organized by theme, such as nature, technology, and business.
- Contributors: The API also provides information about the contributors who have uploaded images and videos to the platform, including their names and profiles.
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: