https://github.com/rajadilipkolli/kafka-experiments

kakfa play ground
https://github.com/rajadilipkolli/kafka-experiments

avro kafka kafka-streams spring-cloud-stream spring-cloud-stream-kafka spring-kafka

Last synced: 17 days ago
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kakfa play ground

• Host: GitHub
• URL: https://github.com/rajadilipkolli/kafka-experiments
• Owner: rajadilipkolli
• License: mit
• Created: 2019-04-14T12:52:24.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2024-10-26T18:26:47.000Z (19 days ago)
• Last Synced: 2024-10-27T06:44:09.590Z (19 days ago)
• Topics: avro, kafka, kafka-streams, spring-cloud-stream, spring-cloud-stream-kafka, spring-kafka
• Language: Java
• Homepage:
• Size: 1.37 MB
• Stars: 6
• Watchers: 5
• Forks: 4
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# Kafka-experiments

**Apache Kafka** is an open-source, distributed streaming platform that enables real-time processing of data streams. It is designed to handle high-throughput, low-latency processing of large volumes of data, making it well-suited for use cases such as real-time analytics, event-driven architectures, and data pipelines.

Kafka is based on a publish-subscribe model, in which producers send data to Kafka topics and consumers subscribe to those topics to receive the data. Kafka stores data in a distributed, partitioned, and replicated log structure, allowing it to scale horizontally and tolerate failures.

Kafka has a number of key features that make it a popular choice for data processing:

  - **Scalability**: Kafka is designed to handle a large volume of data and can scale to handle millions of messages per second.

  - **Durability**: Kafka stores messages on disk, making it possible to recover from failures and maintain data integrity.

  - **Low latency**: Kafka is designed for low-latency processing, making it suitable for real-time applications.

  - **High-throughput**: Kafka can handle high-throughput data streams, allowing it to process large amounts of data in real-time.

  - **Flexibility**: Kafka is highly flexible and can be used for a wide range of data processing use cases, including real-time analytics, data pipelines, and event-driven architectures.

This repository contains sample projects integrating with Kafka using different mechanisms available

  - [Kafka Avro type](./kafka-avro/README.md)

  - [DSL integration](./kafka-dsl-integration/ReadMe.md)

  - [reactor](./kafka-reactor/README.md)

  - [sample](./kafka-sample/README.md)

  - [Examples using spring boot](./kafka-spring-boot/README.md)

  - [Kafka implementation using cloud bindings](./kafka-spring-cloud-sample/README.md)

  - [Kafka streams implementation](./kafka-streams/README.md)

  - [Outbox Pattern Implementation using Modulith](./spring-modulith-outbox-pattern/README.md)

## Reference

Copied and modified from 

 - [sivalabs](https://github.com/sivaprasadreddy/kafka-tutorial)