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Apache Kafka

ASP.NET core +SQL server+Redis+Kafka as a Message Broker

Real-time fraud detection system using PySpark Structured Streaming, Kafka, watermarks, windowing, and Delta Lake.

Real-Time Analytics using Apache Pinot and Apache Druid...

Core data sync engine implementing event-driven processing, rule-based normalization, conflict resolution and audit-ready deterministic pipelines.

Projeto que simula um ecommerce utilizado para estudos utilizando o Apache Kafka.

In real time inference simulator using the MVTec dataset, aproach via DINOv2 and Claude Sonnet 3.5 (Amazon Bedrock's API)

Key platform data integrations repo

Accident Management Service: Emergency Service Module

accident-event-stream

Accident Management Service: Fire Rescue Service Module

Accident Management Service: Law-enforcement service

Accident Management Service: Statistics Service Module

A Project based around a simulated music streaming app (Spotify for example) generating live user events, to practice handling real time streaming of large amounts of data.

This project demonstrates how to build custom Apache Kafka Connect connectors using Java based on Apache Kafka 3. It provides a hands-on guide to implementing both source and sink connectors that can integrate Kafka with custom data sources or destinations not supported by default connectors.

This is a quarkus project that used PostgreSQL database, Hibernate JPA ORM, and apache kafka as a stream messaging. It consist 3 service: code-with-quarkus (product / main ) service, quarkus-create-order service, quarkus-shipping service

Desktop application written in Kotlin that allows for connecting, consuming, and producing to Kafka topics.

The purpose of the project is to supply a quick and easy way to experiment with streaming in a sandbox manner. You can choose to produce files to a topic to replicate live streaming, or consume from a topic.

Workshop for Spring Boot and Kafka

A Spring Cloud Streams workshop using Apache Kafka

The SalesStream dashboards is an application for monitoring and analyzing revenue data in real time. By leveraging the power of Apache Spark and Apache Kafka, this system ensures that financial data is processed efficiently and in a timely manner, providing companies with up-to-date insights into their revenue streams.

Kafka producer and consumer samples using Java and Kotlin. There are two implementations: a simple one and the second using Apache Avro in both languages.