How to load data from ConfigCat to MongoDB

Learn how to use Airbyte to synchronize your ConfigCat data into MongoDB 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 ConfigCat 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 ConfigCat 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 ConfigCat 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.

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 the ConfigCat API

Begin by familiarizing yourself with the ConfigCat API documentation. ConfigCat provides a REST API that allows you to programmatically access feature flags and related configurations. Ensure you understand how to authenticate and retrieve data from the API.

Step 2: Set Up Authentication

Obtain your ConfigCat API key from the ConfigCat dashboard. This API key is essential for making authenticated requests to the ConfigCat API. Store it securely and use it to authorize your API calls.

Step 3: Retrieve Data from ConfigCat

Use an HTTP client (such as `requests` in Python) to make a REST API call to ConfigCat and fetch the data you need. Construct the appropriate GET requests to the relevant endpoints, such as fetching flags, settings, or any other configuration data. Parse the JSON response to extract the necessary details.

Step 4: Transform Data for MongoDB

Once you have the data from ConfigCat, transform it into a format suitable for MongoDB. MongoDB typically handles JSON-like documents, so ensure your data is structured as a dictionary or JSON object. Make necessary adjustments to match your MongoDB schema requirements.

Step 5: Set Up MongoDB Connection

Install a MongoDB client library for your programming language (such as `pymongo` for Python). Establish a connection to your MongoDB database by specifying the connection URI, database name, and any required authentication details.

Step 6: Insert Data into MongoDB

Use the MongoDB client to insert the transformed data into your MongoDB collection. Create or select the appropriate database and collection, then use the `insert_one()` or `insert_many()` methods to add the documents. Check for any errors during insertion and handle them accordingly.

Step 7: Schedule Regular Updates

To keep your MongoDB data up-to-date with ConfigCat, schedule regular data retrieval and insertion tasks. Use a scheduling tool like `cron` (for Unix-based systems) or Task Scheduler (for Windows) to run your script at desired intervals. This ensures that any changes in ConfigCat are reflected in your MongoDB database consistently.

By following these steps, you can successfully transfer data from ConfigCat to MongoDB without relying on third-party connectors or integrations.