3104 Open source projects that are alternatives of or similar to Event Sourcing Jambo

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Springy Store is a conceptual simple μServices-based project using the latest cutting-edge technologies, to demonstrate how the Store services are created to be a cloud-native and 12-factor app agnostic. Those μServices are developed based on Spring Boot & Cloud framework that implements cloud-native intuitive, design patterns, and best practices.

An example of Lightbend's Lagom project with Kotlin

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一个基于.NET Core 3.1的DDD（领域驱动）的极简风WebApi开发框架。

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🦍 The Cloud-Native API Gateway

🚀 Azkarra is a lightweight java framework to make it easy to develop, deploy and manage cloud-native streaming microservices based on Apache Kafka Streams.

A lightweight framework to help creating CQRS and Eventsourcing applications in C#

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我,请始皇[打钱]是一个前后端分离的工具人系统，项目采用 SpringBoot+Go+Vue 开发，项目加入常见的企业级应用所涉及到的技术点，例如 Redis、RabbitMQ 等(主要是多用用工具多踩踩坑)。

Functional API for Microsoft Orleans http://orleanscontrib.github.io/Orleankka/

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Client-side DDD/CQRS for JavaScript.

EventStore Implementation in node.js

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Freedom是一个基于六边形架构的框架，可以支撑充血的领域模型范式。

Domain Driven Design in Python, Ruby and other dynamic languages resources

eSchool Microservice based Solution

Demo applications and code examples for Confluent Platform and Apache Kafka

Mini-Platform致力于更简洁易用的轻量级微服务治理平台。

The boilerplate of the GoLang application with a clear microservices architecture.

A collection of frameworks that I love with a strong focus on clean code, testing, software architecture/design and devops.

Kalium: a reactive framework for micro-services

Uses docker compose with a python flask microservice and MongoDB instance to make a sample application

SpringBoot 整合各类框架和应用

A demo project to show Event Sourcing with Kotlin.

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Stream Store library targeting RDBMS based implementations for .NET

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eventapis is a Java based Event Sourcing framework which can be benefited by the teams who are planning to make CQRS transitions with minimum learning curve and ease of adaptation.

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The purpose of this tiny project is to put things together with the know how that i learned from the course big data expert from formacionhadoop.com The idea is to show how to play with apache spark streaming, kafka,mongo, spark machine learning algorithms.

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Stylish Graph APIs

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