FluxMQ

Comparison

Comprehensive comparison of FluxMQ against industry solutions including EMQX, HiveMQ, Artemis, Mosquitto, NATS, RabbitMQ, and Kafka

Comparison Guide

Last Updated: 2026-02-05

This document provides a basic, evergreen comparison guide without hard claims about third‑party products. Vendor feature sets change frequently; verify details with official docs before making a decision.

FluxMQ Snapshot (from current codebase)

  • Protocols: MQTT 3.1.1/5.0 (TCP, WebSocket), HTTP publish bridge, CoAP publish bridge, AMQP 1.0 and AMQP 0.9.1
  • Queues: Durable queues, consumer groups, ack/nack/reject; stream queues supported; retention policies (time/size/message count)
  • DLQ: Handler exists, automatic DLQ routing not wired yet
  • Clustering: Embedded etcd coordination, gRPC routing, session takeover, hybrid retained storage, optional Raft for queue appends
  • Storage: BadgerDB or in‑memory; pluggable interfaces
  • Security: TLS/mTLS, WebSocket origin validation, rate limiting
  • Observability: OpenTelemetry metrics/tracing (OTLP); no native Prometheus endpoint
  • Clients: Go MQTT client, Go AMQP 0.9.1 client (AMQP 1.0 client not provided)

How to Compare Systems (by category)

MQTT‑Native Brokers

Best fit when:

  • MQTT 5.0 features and device connectivity are the primary focus
  • Edge/IoT workloads need lightweight clients and topic‑based routing

Queue‑Centric Brokers

Best fit when:

  • Work‑queue semantics and explicit acknowledgments are primary
  • Fine‑grained retry/DLQ handling is critical

Log‑Centric Brokers

Best fit when:

  • Long‑term event retention and replay are primary
  • Stream processing and analytics require strong log semantics

Multi‑Protocol Brokers

Best fit when:

  • You need multiple client protocols in a single deployment
  • Cross‑protocol routing and shared durability are important

Decision Checklist

  • Protocols you must support (MQTT, AMQP, HTTP, CoAP)
  • Delivery guarantees required (QoS 0/1/2, at‑least‑once, exactly‑once)
  • Durability and retention needs (time/size retention, replay)
  • Operational complexity you can tolerate (single binary vs external dependencies)
  • Cluster behavior (session takeover, routing, replication strategy)
  • Observability requirements (OTLP, Prometheus, tracing)
  • Client library availability and ecosystem fit

Notes

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