Apache Kafka product ecosystem

Welcome to the Apache Kafka ecosystem.


Service registry graphic - ecosystem overview
Getting started

Red Hat OpenShift Streams for Apache Kafka

Enable your IT development teams to capture, process, and stream real-time data across hybrid cloud environments. The service is based on the open source community project Strimzi and provides developer-friendly features. Strimzi uses Operators to deploy Apache Kafka clusters, connectors, and configurations smoothly and seamlessly on Kubernetes.

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Red Hat OpenShift Connectors

Natively integrated with OpenShift Streams for Apache Kafka, Red Hat OpenShift Connectors provides ready-to-use connectors to import data from external systems into Kafka topics and export data from Kafka topics into external systems. OpenShift connectors enable developers to put a data pipeline in place in just minutes and stream data in near-real time. The service is based on the open source community projects Camel K and Debezium for connectivity and change data capture (CDC) support.

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Red Hat OpenShift Service Registry

OpenShift Service Registry is tightly integrated with OpenShift Connectors and OpenShift Streams and enables development teams to publish, discover, and communicate using well-defined data schemas with Apache Kafka. OpenShift Service Registry improves service resiliency by enforcing schema versioning rules and boosts application efficiency by decoupling the schema from client applications and reducing payload sizes. The service is based on the open source community project Apicurio.

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Red Hat AMQ Streams

The AMQ Streams component is a scalable, distributed, and high-performance data streaming platform based on Apache Kafka. IT developer teams can install, configure, and manage Apache Kafka on Kubernetes for streaming data between microservices and other applications. The product is based on the open source community projects Apache Kafka and Strimzi.

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Streams processing with Kafka Streams

Kafka Streams is a library for writing and creating pipelines to process data streams coming from and to Kafka topics. Learn how to set up telemetry for a video game using Kafka Streams, Quarkus, and Red Hat OpenShift Streams for Apache Kafka.

Watch Game telemetry with Kafka Streams and Quarkus! 

This video by Evan Shortiss shows how to set up a development environment to analyze real-time gaming data and how to use game data analysis and telemetry data to improve a product.

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Red Hat Cloud Services are open source

Apache Kafka

Apache Kafka is an open source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. 

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Debezium is an open source distributed platform for change data capture. Point it at databases, and applications can start responding in real-time to all of the inserts, updates, and deletes that other applications commit. 

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Apache Camel K

Application platform for hosting apps with Apache Camel K is a lightweight integration framework built from Apache Camel that runs natively on Kubernetes and is specifically designed for serverless and microservice architectures. 

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Apicurio is an API and schema registry for microservices. You can use the Apicurio Registry to store and retrieve service artifacts such as OpenAPI specifications and AsyncAPI definitions, as well as schemas such as Apache Avro, JSON, and Google Protocol Buffers. 

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Strimzi provides a way to run an Apache Kafka cluster on Kubernetes in various deployment configurations. For development, it’s easy to set up an instance in Minikube in a few minutes. 

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