Kafka integrations to save data teams 40 hours a week

Modernize your data infrastructure with Airbyte's high speed data replication. Move large volumes of data with best-in-class CDC methods and replicate large databases within minutes.

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Scale your data integration with confidence

Start using Kafka integrations in three easy steps

Integrate Kafka connector in Airbyte

Choose a source connector to extract data

Connect Kafka as a source in Airbyte to start the data extraction process - without deep technical expertise.

Choose a source connector from 400+ integrations available on Airbyte to start the data extraction process - without deep technical expertise.

Send Kafka data anywhere you need it

Store your data inside Kafka destination

Choose from 50+ Airbyte destinations, including warehouses, databases, and lakes, to store and analyze your Kafka data.

Choose Kafka from 50+ Airbyte destinations, including warehouses, databases, and lakes, to store and analyze the data from the source connector.

Configure your Kafka data synchronization

Configure the integration for data synchronization

Select the Kafka streams you need and define your sync frequency. Airbyte lets you choose exactly which data to load and where it lands for full pipeline control.

Select the streams you need and define your sync frequency. Airbyte lets you choose exactly which data to load and where it lands for full pipeline control.

Kafka integrations let you do all these

Sync Kafka data to BigQuery for advanced analytics

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Replicate Kafka data into PostgreSQL for structured querying

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Get insights by merging Kafka data with HubSpot

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Export Kafka data to Google Sheets for analysis

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Kafka integrations let you do all these

Sync Google Analytics data to Kafka for analysis

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Load PostgreSQL data in to Kafka effortlessly

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Keep Notion data fresh in Kafka with automated syncs

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Manage Salesforce data in Kafka BigQuery for analytics

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All about Kafka integrations

What are Kafka integrations?

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.

Why choose Airbyte for Kafka data integration?

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.

What data can you extract from Airbyte’s Kafka integration?

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.

What data can you load to Kafka?

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.

How often does Airbyte sync my Kafka data?

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.

Do I need coding experience to use the Kafka integrations?

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.

About Kafka

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.