Scale your data integration with confidence

Choose a source connector to extract data
Choose a source connector from 400+ integrations available on Airbyte to start the data extraction process - without deep technical expertise.
The Kafka integrations in Airbyte allows users to sync data to Kafka, where each stream is written to its corresponding Kafka topic. This enables seamless integration and data flow between various sources and Kafka for real-time processing and analytics.
Choosing Airbyte for Kafka data integration offers a user-friendly open-source platform that simplifies the process of connecting diverse data sources to Kafka. With robust capabilities, Airbyte ensures high sync success rates, supports dynamic topic configurations, and provides extensive documentation for ease of setup.
Airbyte’s Kafka integration currently supports data in JSON format. Each record output to Kafka includes essential fields like the unique UUID assigned by Airbyte, the timestamp of when the event was pulled, and the actual event data in JSON form, ensuring comprehensive tracking and data integrity.
Airbyte’s Kafka integration currently supports data in JSON format. Each record output to Kafka includes essential fields like the unique UUID assigned by Airbyte, the timestamp of when the event was pulled, and the actual event data in JSON form, ensuring comprehensive tracking and data integrity.
Airbyte supports incremental append sync for Kafka data, which allows for efficient updates without needing to perform full refresh syncs. This approach optimizes data transfer, enabling timely and resource-efficient updates as new data becomes available.
No coding experience is necessary to use the Kafka integrations with Airbyte. The platform is designed for users of all technical levels, with a straightforward UI that guides users through the setup and configuration process, making it accessible to everyone.



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Kafka is a distributed event streaming platform enabling real-time data pipelines and applications. Integrating Kafka data allows data engineers to efficiently process and analyze vast data streams, ensuring low-latency data integration, enhancing scalability, and facilitating real-time analytics. This empowers organizations to make informed, data-driven decisions swiftly.



