How to load data from Xero to S3 Glue

Learn how to use Airbyte to synchronize your Xero data into S3 Glue within minutes.

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.

Building in-house pipelines
Bespoke pipelines are:
  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.
After Airbyte
Airbyte connections are:
  • Reliable and accurate
  • Extensible and scalable for all your needs
  • Deployed and governed your way
All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and AI Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Xero connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up S3 Glue for your extracted Xero data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Xero to S3 Glue in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Setup Complexities simplified!

You don’t need to put hours into figuring out how to use Airbyte to achieve your Data Engineering goals.

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

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Raman Singh

Tech Lead at Symend

Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

Learn more
Chase Zieman headshot

Chase Zieman

Chief Data Officer

“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.”

Learn more

Rupak Patel

Operational Intelligence Manager

"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."

Learn more

How to Sync to Manually

Step 1: Extract Data from Xero API

Begin by accessing the Xero API to extract the data you need. You'll need to register your application with Xero to obtain the necessary OAuth2.0 credentials (client ID and client secret). Use these credentials to authenticate and make API requests. You can use a programming language like Python to interact with the API. Fetch the data in the desired format, such as JSON or CSV.

Once you have extracted the data from Xero, you may need to transform it into a format that’s suitable for your analysis or storage needs. This can include cleaning the data, normalizing fields, and converting it into a flat file format like CSV or Parquet. Use Python libraries like Pandas for this task.

Log into your AWS Management Console and navigate to Amazon S3. Create a new S3 bucket if you haven't already. This bucket will be used to store the transformed data files. Make sure to configure the appropriate permissions for your bucket, ensuring that it can be accessed by AWS Glue.

After transforming the data, the next step is to upload it to your S3 bucket. You can use the AWS CLI, Boto3 (AWS SDK for Python), or the AWS Management Console to upload the files. Ensure the files are named and organized according to your data management strategy.

In the AWS Management Console, navigate to AWS Glue and create a new crawler. Configure the crawler to point to your S3 bucket where the data is stored. The crawler will automatically scan your data files, infer their schema, and populate the AWS Glue Data Catalog with tables that represent your data.

With your data cataloged, you can set up an AWS Glue ETL job to further transform and process the data if necessary. Define the source (S3 location), the transformation logic (using PySpark or Scala), and the target (another S3 bucket or a data warehouse like Amazon Redshift). Schedule the job to run at your desired frequency.

Finally, ensure that you monitor the ETL jobs and crawlers for successful execution. Set up CloudWatch alarms and logging to track the performance and catch any errors. Regular maintenance, such as updating scripts and managing data lifecycle policies on S3, will ensure the process remains efficient over time.

By following these steps, you can effectively transfer data from Xero to Amazon S3 using AWS Glue, without relying on third-party connectors or integrations.