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RabbitMQ vs SQS: broker self-run ou fila gerenciada?

RabbitMQ é um broker rico em recursos que você mesmo opera; Amazon SQS é uma fila totalmente gerenciada com recursos mínimos mas operação quase zero.

RabbitMQ oferece exchanges, roteamento flexível, prioridades e suporte a protocolos (AMQP, MQTT, STOMP), mas você o roda e escala. SQS é uma fila simples, durável e totalmente gerenciada (standard ou FIFO) que escala automaticamente e integra fortemente com a AWS, trocando roteamento avançado por simplicidade operacional. RabbitMQ favorece recursos e controle; SQS favorece zero-ops dentro da AWS.

RabbitMQSQS
OpsAutogerenciadoTotalmente gerenciado (AWS)
RoteamentoRico (exchanges)Básico (queue/FIFO)
ProtocolosAMQP, MQTT, STOMPAWS API
EscalaManual / clusterAutomática
Melhor paraRoteamento complexo, controleAWS-native, baixa ops

Caso de uso e ops

RabbitMQ se adequa a times que precisam de roteamento rico, prioridades ou portabilidade fora da AWS e dispostos a rodar um broker. SQS se adequa a sistemas AWS-native que querem uma fila durável sem manutenção e semântica simples de producer/consumer, aceitando roteamento limitado e lock-in da AWS.

Em CI

RabbitMQ roda como service container para testes de integração. SQS pode ser emulado com LocalStack ou ElasticMQ para que os testes rodem offline. Ambos se adequam a runners gerenciados, onde runners mais rápidos encurtam a inicialização do emulador/broker e a execução dos testes.

Decide with your own numbers, not a feature table

Feature comparisons age badly and rarely decide anything, because both tools in a mature category can do the job. What differs is how each behaves on your repository, and that takes one afternoon to measure.

Terminal
# time a cold install with each candidate, cache cleared
hyperfine --prepare "rm -rf node_modules" --warmup 1 \
  "<tool-a> install" "<tool-b> install"

# and the thing CI actually pays for: a cold run with no local cache
docker run --rm -v "$(pwd):/w" -w /w node:22 sh -c "<tool> install"

What actually changes when you switch

  • Lockfile format. A switch is a one-way door for anyone still on the old tool until everyone migrates, so plan it as a single coordinated change.
  • Resolution strictness. Tools differ on whether an undeclared transitive import works, and the stricter one will surface latent bugs as new failures.
  • CI cache configuration. The cache path and key differ per tool; carrying over the old ones silently disables caching.
  • Everyone on the team and every runner must move together. Pin the version so they cannot drift.

O veredito

Roteamento complexo, prioridades ou mensageria portável entre nuvens: RabbitMQ, aceitando o ônus operacional. Enfileiramento durável AWS-native com zero manutenção: SQS. O fator decisivo costuma ser quanta flexibilidade de roteamento você precisa versus quanto você valoriza zero-ops dentro da AWS.

Perguntas frequentes

RabbitMQ vs SQS: Self-Run Broker or Managed Queue?
RabbitMQ offers exchanges, flexible routing, priorities, and protocol support (AMQP, MQTT, STOMP), but you run and scale it. SQS is a simple, durable, fully managed queue (standard or FIFO) that scales automatically and integrates tightly with AWS, trading advanced routing for operational simplicity.
Use case and ops?
RabbitMQ suits teams needing rich routing, priorities, or non-AWS portability and willing to run a broker. SQS suits AWS-native systems that want a durable queue with no maintenance and simple producer/consumer semantics, accepting limited routing and AWS lock-in.
In CI?
RabbitMQ runs as a service container for integration tests. SQS can be emulated with LocalStack or ElasticMQ so tests run offline. Both fit managed runners, where faster runners shorten emulator/broker startup and test execution.
Which should I choose?
Complex routing, priorities, or cloud-portable messaging: RabbitMQ, accepting the operational burden. AWS-native, durable queuing with zero maintenance: SQS. The deciding factor is usually how much routing flexibility you need versus how much you value zero-ops within AWS.

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