How to load data from Zendesk Support to Google Firestore

Learn how to use Airbyte to synchronize your Zendesk Support data into Google Firestore within minutes.

Summarize this article with:

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.

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 Zendesk Support connector in Airbyte

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

Set up Google Firestore for your extracted Zendesk Support data

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

Configure the Zendesk Support to Google Firestore 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

Andre Exner

Director of Customer Hub and Common Analytics

"For TUI Musement, Airbyte cut development time in half and enabled dynamic customer experiences."

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 Zendesk Support to Google Firestore Manually

Begin by enabling API access in your Zendesk account. Go to the Admin Center, select "Channels" and then "API". Ensure that API access is enabled and note down your subdomain, email, and API token. These credentials will be used to authenticate requests to the Zendesk API.

Access your Google Cloud Console and create a new project if you haven't already. Enable Firestore by navigating to Firestore in the left-hand menu and selecting "Create Database". Choose a start mode (production or test) and note the database settings. Ensure you have the necessary permissions to write data to Firestore.

On your local machine or server, ensure you have a development environment set up with Node.js or Python (or any preferred programming language that supports HTTP requests and JSON). Install the required libraries for making HTTP requests and for interacting with Firestore. For example, in Node.js, you might use Axios for HTTP requests and the Firebase Admin SDK for Firestore.

Write a script to fetch data from Zendesk using its REST API. Use HTTP GET requests to access the desired endpoints (e.g., tickets, users). Authenticate your requests using Basic Auth with your Zendesk email/token. Parse the JSON response to extract the data you need.

Example in Node.js:
```javascript
const axios = require('axios');
const zendeskDomain = 'your_subdomain.zendesk.com';
const zendeskEmail = 'your_email/token';
const zendeskToken = 'your_api_token';

async function fetchZendeskData() {
const response = await axios.get(`https://${zendeskDomain}/api/v2/tickets.json`, {
auth: {
username: zendeskEmail,
password: zendeskToken
}
});
return response.data.tickets;
}
```

Process the fetched data to fit the structure required by Firestore. This may involve transforming the data format or filtering out unnecessary fields. Ensure that your data is in JSON format, as this is compatible with Firestore.

Use Firebase Admin SDK to authenticate and initialize Firestore in your script. Download the service account key from your Google Cloud project and load it in your script for authentication.

Example in Node.js:
```javascript
const admin = require('firebase-admin');
const serviceAccount = require('./path/to/serviceAccountKey.json');

admin.initializeApp({
credential: admin.credential.cert(serviceAccount)
});

const db = admin.firestore();
```

Write the processed data to Firestore by specifying the collection and documents you want to create or update. Use Firestore methods to add data, ensuring that data types are compatible with Firestore's data model.

Example in Node.js:
```javascript
async function uploadToFirestore(tickets) {
const batch = db.batch();
tickets.forEach((ticket) => {
const ticketRef = db.collection('tickets').doc(ticket.id.toString());
batch.set(ticketRef, ticket);
});
await batch.commit();
console.log('Data successfully written to Firestore');
}

async function main() {
const tickets = await fetchZendeskData();
await uploadToFirestore(tickets);
}

main().catch(console.error);
```

By following these steps, you can transfer data from Zendesk Support to Google Firestore without relying on third-party connectors or integrations, using the powerful capabilities of APIs and custom scripting.

How to Sync Zendesk Support to Google Firestore Manually - Method 2:

FAQs

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.

Zendesk Support is a software designed to help businesses manage customer interactions. It provides businesses with the means to personalize support across any channel with the ability to prioritize, track and solve customer issues. Also built for iOS, Zendesk Support can be accessed on iPhone and iPad, adding a new dimension to the ability to add the necessary people to a customer conversation at any time.

Zendesk Support's API provides access to a wide range of data related to customer support and service management. The following are the categories of data that can be accessed through the API:  

1. Tickets: Information related to customer inquiries, including ticket ID, subject, description, status, priority, and tags.  
2. Users: Data related to customer profiles, including name, email, phone number, and organization.  
3. Organizations: Information about customer organizations, including name, domain, and tags.  
4. Groups: Data related to support groups, including name, description, and membership.  
5. Views: Information about support views, including name, description, and filters.  
6. Macros: Data related to macros, including name, description, and actions.  
7. Triggers: Information about triggers, including name, description, and conditions.  
8. Custom Fields: Data related to custom fields, including name, type, and options.  
9. Attachments: Information about attachments, including file name, size, and content.  
10. Comments: Data related to ticket comments, including author, body, and timestamp.  Overall, Zendesk Support's API provides access to a comprehensive set of data that can be used to manage and optimize customer support and service operations.

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: 
1. Set up Zendesk Support to Google Firestore as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Zendesk Support to Google Firestore and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

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.

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:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter