How to load data from Pendo to Firebolt

Learn how to use Airbyte to synchronize your Pendo data into Firebolt 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 Pendo connector in Airbyte

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

Set up Firebolt for your extracted Pendo 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 Pendo to Firebolt 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: Understand Pendo's API Documentation

Begin by familiarizing yourself with Pendo's API documentation. This will help you understand the available endpoints, authentication methods, and the structure of the data you can extract. You will likely need API keys or tokens to access data.

Step 2: Extract Data from Pendo

Use a scripting language like Python to connect to Pendo's API and extract the data you need. Construct API requests to fetch the required data, such as user events or analytics. Ensure you handle pagination if the data set is large, using loops or recursive functions to fetch all pages of data.

Step 3: Transform Data to a Suitable Format

Once you have extracted the data, transform it into a format that is compatible with Firebolt. This typically involves converting JSON responses from the API into CSV or Parquet format, which are commonly used for data ingestion into databases. Use libraries like pandas in Python to manipulate and format the data.

Step 4: Set Up a Firebolt Account and Database

If not already done, create an account with Firebolt and set up the necessary database and table structures to accommodate the incoming data. Define schemas that match the data structure you extracted from Pendo to ensure smooth ingestion.

Step 5: Upload Data to a Cloud Storage Location

Firebolt requires data to be uploaded to a cloud storage service like Amazon S3 before it can be ingested. Use AWS CLI or SDKs to upload your formatted data from your local environment to an S3 bucket. Ensure that you have the correct permissions to access and upload files to the bucket.

Step 6: Ingest Data into Firebolt

With the data available in your cloud storage, use Firebolt's SQL commands to ingest the data into your Firebolt database. Write SQL COPY statements to load data from your S3 bucket into the appropriate tables in Firebolt. Ensure that you specify the correct file format, delimiter, and other necessary parameters in your SQL commands.

Step 7: Verify Data Integrity and Consistency

After ingesting the data, perform checks to verify the integrity and consistency of the data in Firebolt. Run queries to compare record counts, check for duplicates, and ensure that all expected fields have been populated correctly. This step is crucial to confirm that the migration was successful and the data is ready for analysis or further processing.

By following these steps, you can effectively move data from Pendo to Firebolt without relying on third-party connectors or integrations.