How to load data from Chargebee to BigQuery
Learn how to use Airbyte to synchronize your Chargebee data into BigQuery 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
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
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
- Login to your Chargebee account to access its web interface.
- Look at the right-hand navigation bar on the home page and click on Settings options.
- Click on the Import & Export Data option from the dropdown menu.
- You’ll see an Export Chargebee data section. There, click on the Export data button.
- Now, you can export the data you want, including invoice data, transactions, product catalog, and subscription data.
- After selecting the export data, click the Select Criteria to export button.
- Next, it'll give you a popup menu that previews data where you can add certain filters and conditions according to your business requirements. You can also choose to export data in default configurations.
- Lastly, click on the Export option, and it will start preparing your data and download it on a zip file on your local machine.
- Go to the zip file you downloaded on your local machine and extract it to obtain a CSV file with the data on it.
- Verify the data in the CSV file and structure it as per your ideal format if necessary.
- Now, we will use Google Drive as a mediator to upload the CSV file to BigQuery easily.
- To perform this task, log in to your Google Drive account.
- From the top left corner, click on the +New button. Then, from the dropdown menu, select File Upload.
- Choose the CSV file you downloaded from Step 1 and upload it.
- After the upload is successful, copy the link to the file destination in Google Drive.
- Login to your Google Cloud console and navigate to the BigQuery page.
- In the Explorer pane from the left side, create a new project or select an existing one in BigQuery.
- Click on the Create dataset option to create a new database under your current project.
- Now provide a unique Dataset name, and fill in other configuration details per your requirements. Click CREATE DATASET.
- Right-click on the Dataset you just created and click +Create table.
- In the Create table section, give your table a unique name.
- Select Drive as the source. In the Select Drive URI field, paste the link to the file you uploaded to Google Drive from Step 2, and set the file format to CSV.
- Configure other details and click CREATE TABLE.
- Ensure the destination is the project and database you created in BigQuery.
- Now, BigQuery will automatically import the data file you exported from Step 1.
- Verify the table's structure and tweak the formatting according to your requirements.