How to load data from Pendo to MongoDB

Learn how to use Airbyte to synchronize your Pendo data into MongoDB within minutes.

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Bespoke pipelines are:
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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 MongoDB 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 MongoDB 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.

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

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How to Sync to Manually

Step 1: Understand Pendo's API

Begin by familiarizing yourself with Pendo's API documentation. Pendo provides RESTful APIs that allow you to extract data such as analytics, user details, and other relevant information. Understanding the available endpoints, authentication methods, and rate limits is essential to effectively pull data.

Step 2: Set Up API Authentication

To access Pendo's data, you'll need to authenticate your requests. Typically, Pendo uses API keys for authentication. Locate your API key in the Pendo dashboard or request one from your administrator. Ensure that you securely store this key and include it in the headers of your HTTP requests.

Step 3: Extract Data from Pendo

Using a programming language like Python, set up scripts to make HTTP GET requests to Pendo's API endpoints. Use libraries such as `requests` in Python to handle these requests. Start by extracting a small dataset to verify your connection and understand the structure of the data returned.

Step 4: Prepare Data for MongoDB

Once you have the data, you may need to transform or clean it to fit your MongoDB schema. Use Python libraries like `pandas` to manipulate your data as required. This step might involve flattening nested structures or converting data types to match MongoDB's requirements.

Step 5: Install and Configure MongoDB

Ensure that MongoDB is installed and running on your local machine or server. Use the MongoDB shell or GUI clients like MongoDB Compass to create the necessary databases and collections where you intend to store your Pendo data.

Step 6: Load Data into MongoDB

Use a MongoDB client library, such as `pymongo` in Python, to connect to your MongoDB instance. Insert the processed data into the appropriate collections. Ensure that you handle any potential errors, such as duplicate keys or connectivity issues, during the insertion process.

Step 7: Automate and Schedule Data Transfers

To keep your data current, automate the extraction and loading process. Use task schedulers like `cron` on Unix systems or Task Scheduler on Windows to run your data extraction and loading scripts at regular intervals. Ensure that your scripts are robust, with logging and error handling, to manage any issues during automation.

By following these steps, you can manually transfer data from Pendo to MongoDB, ensuring that you have control over every part of the process without relying on third-party solutions.