How to load data from Cart.com to Kafka
Learn how to use Airbyte to synchronize your Cart.com data into Kafka 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
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
After Airbyte
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes



Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
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
Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

Chase Zieman

“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.”

Rupak Patel
"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."
How to Sync to Manually
Step 1: Understand Your Cart System's Data Export Capabilities
First, familiarize yourself with how your cart system allows data exports. Determine if it can generate data files (like CSV, JSON, or XML) or if it has APIs available for data retrieval. Understanding these options will dictate how you can extract data from the cart system.
Step 2: Set Up a Data Export Script
Write a script in a language of your choice (such as Python, Java, or Node.js) that can interface directly with your cart system. This script should be able to either export data files or call the cart system's APIs to retrieve the necessary data. Ensure the script can be scheduled to run at regular intervals if periodic data transfer is required.
Step 3: Transform Cart Data to Kafka-Compatible Format
Once the data is exported from the cart system, transform it into a format suitable for Kafka. JSON is a commonly used format for Kafka messages. Your script should include a transformation step that converts the data to JSON, ensuring that the data adheres to a consistent schema for easy processing downstream.
Step 4: Install and Configure Kafka Client
Install a Kafka client library in your environment. Choose a client library that is compatible with your chosen programming language. Configure the library with the necessary Kafka broker details, such as broker address, topic name, and any required authentication settings.
Step 5: Write Data to Kafka Topics
Extend your script to include functionality for producing messages to Kafka. Use the Kafka client library to send the transformed JSON data to the appropriate Kafka topic. Ensure that each message is sent with the correct key if message partitioning is required.
Step 6: Implement Error Handling and Logging
Incorporate error handling in your script to manage any issues that may arise during data extraction, transformation, or transmission to Kafka. Implement logging to capture both successful operations and errors, which will aid in monitoring and troubleshooting the data pipeline.
Step 7: Schedule and Automate the Data Transfer
Finally, automate your script using a task scheduler like cron (on Unix-based systems) or Task Scheduler (on Windows). Set it to run at the desired frequency to ensure continuous data movement from the cart to Kafka. Monitor the process regularly to ensure it operates smoothly and adjust as necessary based on data volume or system changes.
By following these steps, you can establish a direct pipeline for moving data from a shopping cart system to Kafka without relying on third-party connectors or integrations.