This guide introduces NanoMQ, a lightweight high‑performance MQTT broker for edge and IoT scenarios, outlines its key features, core advantages, and provides step‑by‑step Docker deployment, client connection, and publishing examples with PHP code.
This article provides a detailed, step‑by‑step analysis of RabbitMQ's classic queue storage architecture, covering directory layout, index and data file formats, write and read workflows, file compaction, and practical operational tips such as publisher confirms and manual acknowledgments to improve reliability and throughput.
This article explains the lightweight publish/subscribe MQTT protocol, its origin, key features, usage scenarios, differences from traditional message queues, topic structures and wildcards, as well as practical client tools like Mosquitto and MQTTX with configuration examples.
This article explains RabbitMQ's transaction mechanism, outlines its basic workflow, core channel methods, provides a Java example, compares its advantages and disadvantages with the confirm mode, and offers guidance on choosing the appropriate approach for different scenarios.
This guide explains how to enable MQTT support in RabbitMQ, use MQTTBox and MQTT.js for instant messaging, and integrate MQTT into a SpringBoot application, providing step‑by‑step commands, code snippets, and configuration details for both front‑end and back‑end developers.
This article examines synchronous versus asynchronous microservice communication, outlines the benefits of async messaging, and compares three popular message brokers—RabbitMQ, Kafka, and Redis—by evaluating their scale, persistence, consumer models, and ideal use cases to help developers choose the right solution.
This article explains RocketMQ's broker storage architecture, detailing the roles of CommitLog, ConsumeQueue, and IndexFile, and describes how messages are formatted, indexed, and written to disk using memory‑mapped files to achieve high throughput and reliability.
This tutorial walks through downloading compatible Erlang versions, installing RabbitMQ on Windows, starting the service, verifying its status, and accessing the management UI with default credentials, providing a complete setup for backend development with RabbitMQ.
This article explains why forward and backward compatibility are crucial for evolving systems, covering database encoding, schema evolution, REST and RPC communication, message brokers, and actor frameworks, and provides practical guidance for designing compatible data flows across services.
This article compares three popular open‑source message brokers—RabbitMQ, Kafka, and Redis—examining their scalability, persistence, consumer models, and ideal use cases to help developers select the most suitable asynchronous communication solution for their microservice architecture.
This article explains the core concepts of message queues—including producers, consumers, messages, brokers, and push/pull delivery—and analyzes three consumption scenarios: at‑most‑once, at‑least‑once, and exactly‑once, detailing the required producer, broker, and consumer behaviors for each.
This article explains how EMQX 3.0 maintains routing and distribution layers, detailing the subscriber tables, shared‑subscription handling, topic‑trie structures, route look‑ups, and the Erlang code that drives message matching and dispatch across a clustered broker.
This article explains how modern message middleware works by describing the two primary communication styles—message queuing and publish‑subscribe—illustrating each with examples, comparing their characteristics, and listing common middleware products to help developers choose the appropriate solution for their backend systems.
This article explains how message brokers like RabbitMQ use the AMQP protocol to enable efficient communication in distributed systems, covering core concepts, queue and exchange configurations, four routing patterns, and message acknowledgment strategies.
This article introduces Celery, a Python‑based distributed task queue, explains its three‑part architecture, shows how to install RabbitMQ and Celery on an AWS EC2 Linux instance, and provides step‑by‑step code examples for defining tasks, running workers, and retrieving asynchronous results.
Disque, an open‑source distributed in‑memory message broker created by Redis's creator, offers synchronous replication, flexible delivery semantics, multi‑master clustering, and fine‑grained job control, but remains in Alpha with several limitations that make it unsuitable for production use today.
