Trusted by data-driven companies
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 reviewing Xero's API documentation to understand how to authenticate and retrieve data. You'll need to use OAuth 2.0 for authentication, so familiarize yourself with the necessary endpoints and required scopes for accessing the data you need.
Log in to the Xero Developer portal and create a new application. Provide necessary details and register your application to obtain the client ID and client secret. These credentials will be used to authenticate your requests to the Xero API.
Implement OAuth 2.0 authentication in your application to obtain an access token. This involves redirecting the user for authorization, receiving a code, and exchanging it for an access token. Use libraries like `requests` in Python or equivalent in other languages to handle HTTP requests.
Use the access token to make API calls to Xero and retrieve the necessary data. Make GET requests to the relevant endpoints, such as invoices, contacts, or transactions. Handle pagination and rate limits as per Xero's API guidelines to ensure you retrieve all required data.
Process and transform the data into a format suitable for storage in S3, such as CSV or JSON. This may involve parsing the API response and writing it to a file. Ensure that the file format and structure meet your data analysis or storage requirements.
Log in to your AWS Management Console and create an S3 bucket where you'll store the Xero data. Configure bucket permissions and set up an appropriate policy to allow access to your application, ensuring data security and compliance with your organization's standards.
Use AWS SDKs (such as Boto3 for Python) or AWS CLI to upload the transformed data files to your S3 bucket. Write a script or use a command to automate the upload process, specifying the file path and S3 bucket details. Verify that the data has been successfully uploaded and is accessible in your S3 bucket.
By following these steps, you can efficiently move data from Xero to Amazon S3 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.
Xero is the online accounting software for your business which connects you to your accountant, bank, bookkeeper, and other business apps. Xero is an well known accounting system that have designed for small and growing businesses with their trusted advisors. You don't need to have an accounting degree to use the Xero Accounting app for a small business owner. It is also a cloud-based small business accounting software having tools for managing bank reconciliation, inventory, invoicing, purchasing, expenses.
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:
