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  1. Stackups
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  4. Message Queue
  5. Apache RocketMQ vs RabbitMQ

Apache RocketMQ vs RabbitMQ

OverviewDecisionsComparisonAlternatives

Overview

RabbitMQ
RabbitMQ
Stacks21.8K
Followers18.9K
Votes558
GitHub Stars13.2K
Forks4.0K
Apache RocketMQ
Apache RocketMQ
Stacks48
Followers200
Votes8

Apache RocketMQ vs RabbitMQ: What are the differences?

Apache RocketMQ and RabbitMQ are both robust messaging systems. Let's explore the key differences between them.

  1. Deployment Model: Apache RocketMQ has a distributed deployment model where message brokers are deployed across different machines, enabling easy scalability and fault tolerance. On the other hand, RabbitMQ uses a centralized deployment model where a single message broker manages all the incoming messages.

  2. Language Support: Apache RocketMQ supports multiple languages such as Java, C++, and Python, making it versatile for developers. In contrast, RabbitMQ primarily focuses on supporting the AMQP (Advanced Message Queuing Protocol), limiting its language support to languages with AMQP client libraries.

  3. Persistence: Apache RocketMQ provides built-in persistence for messages, ensuring that the messages are stored on disk even in case of server failure. RabbitMQ, on the other hand, relies on external persistence mechanisms like databases or disk drives for message persistence.

  4. Message Routing: Apache RocketMQ uses a topic-based message routing model, where messages are organized into topics and subscribers can subscribe to specific topics. RabbitMQ follows a direct exchange and fanout exchange routing model, allowing messages to be sent directly to specific queues or broadcasted to all queues respectively.

  5. Message Ordering: Apache RocketMQ guarantees message ordering within a queue, ensuring that messages are consumed in the same order they were produced. However, RabbitMQ does not provide strict ordering guarantees, as it prioritizes message delivery over maintaining the order of messages.

  6. Protocol Compatibility: Apache RocketMQ supports both the AMQP and MQTT (Message Queuing Telemetry Transport) protocols, allowing interconnectivity with systems that use these protocols. In contrast, RabbitMQ primarily focuses on AMQP and lacks native support for MQTT.

In summary, Apache RocketMQ emphasizes high performance and fault tolerance, making it suitable for large-scale distributed systems, while RabbitMQ's versatility and extensive protocol support make it a popular choice for various messaging scenarios.

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Advice on RabbitMQ, Apache RocketMQ

viradiya
viradiya

Apr 12, 2020

Needs adviceonAngularJSAngularJSASP.NET CoreASP.NET CoreMSSQLMSSQL

We are going to develop a microservices-based application. It consists of AngularJS, ASP.NET Core, and MSSQL.

We have 3 types of microservices. Emailservice, Filemanagementservice, Filevalidationservice

I am a beginner in microservices. But I have read about RabbitMQ, but come to know that there are Redis and Kafka also in the market. So, I want to know which is best.

933k views933k
Comments
Pulkit
Pulkit

Software Engineer

Oct 30, 2020

Needs adviceonDjangoDjangoAmazon SQSAmazon SQSRabbitMQRabbitMQ

Hi! I am creating a scraping system in Django, which involves long running tasks between 1 minute & 1 Day. As I am new to Message Brokers and Task Queues, I need advice on which architecture to use for my system. ( Amazon SQS, RabbitMQ, or Celery). The system should be autoscalable using Kubernetes(K8) based on the number of pending tasks in the queue.

474k views474k
Comments
Kirill
Kirill

GO/C developer at Duckling Sales

Feb 16, 2021

Decided

Maybe not an obvious comparison with Kafka, since Kafka is pretty different from rabbitmq. But for small service, Rabbit as a pubsub platform is super easy to use and pretty powerful. Kafka as an alternative was the original choice, but its really a kind of overkill for a small-medium service. Especially if you are not planning to use k8s, since pure docker deployment can be a pain because of networking setup. Google PubSub was another alternative, its actually pretty cheap, but I never tested it since Rabbit was matching really good for mailing/notification services.

266k views266k
Comments

Detailed Comparison

RabbitMQ
RabbitMQ
Apache RocketMQ
Apache RocketMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Apache RocketMQ is a distributed messaging and streaming platform with low latency, high performance and reliability, trillion-level capacity and flexible scalability.

Robust messaging for applications;Easy to use;Runs on all major operating systems;Supports a huge number of developer platforms;Open source and commercially supported
-
Statistics
GitHub Stars
13.2K
GitHub Stars
-
GitHub Forks
4.0K
GitHub Forks
-
Stacks
21.8K
Stacks
48
Followers
18.9K
Followers
200
Votes
558
Votes
8
Pros & Cons
Pros
  • 235
    It's fast and it works with good metrics/monitoring
  • 80
    Ease of configuration
  • 60
    I like the admin interface
  • 52
    Easy to set-up and start with
  • 22
    Durable
Cons
  • 9
    Too complicated cluster/HA config and management
  • 6
    Needs Erlang runtime. Need ops good with Erlang runtime
  • 5
    Configuration must be done first, not by your code
  • 4
    Slow
Pros
  • 2
    Support tracing message and transactional message
  • 2
    Million-level message accumulation capacity in a single
  • 1
    Feature-rich administrative dashboard for configuration
  • 1
    BigData Friendly
  • 1
    High throughput messaging
Integrations
No integrations available
Docker
Docker

What are some alternatives to RabbitMQ, Apache RocketMQ?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

Celery

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

Amazon SQS

Amazon SQS

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

ActiveMQ

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

ZeroMQ

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Gearman

Gearman

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

IronMQ

IronMQ

An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.

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