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  4. Message Queue
  5. ActiveMQ vs RabbitMQ

ActiveMQ vs RabbitMQ

OverviewDecisionsComparisonAlternatives

Overview

RabbitMQ
RabbitMQ
Stacks21.8K
Followers18.9K
Votes558
GitHub Stars13.2K
Forks4.0K
ActiveMQ
ActiveMQ
Stacks879
Followers1.3K
Votes77
GitHub Stars2.4K
Forks1.5K

ActiveMQ vs RabbitMQ: What are the differences?

Introduction

ActiveMQ and RabbitMQ are both message broker platforms that provide reliable messaging between applications. However, there are several key differences between these two platforms that make them suitable for different use cases.

  1. Language Support: One major difference between ActiveMQ and RabbitMQ is the language support they provide. ActiveMQ supports multiple language bindings, including Java, C++, .NET, and many others. On the other hand, RabbitMQ primarily focuses on supporting the Advanced Message Queuing Protocol (AMQP), but provides official client libraries for various programming languages such as Java, Python, and .NET.

  2. Ease of Use: ActiveMQ is known for its user-friendly and intuitive interface, making it easy for developers to set up and configure. It also offers a wide range of features out of the box, such as message persistence, message cursors, and distributed queues. RabbitMQ, on the other hand, requires more configuration and management, especially when deploying it in a clustered environment. It offers a more lightweight and modular architecture, which can be highly customized based on specific requirements.

  3. Message Persistence: ActiveMQ provides built-in message persistence by default, allowing messages to be stored on disk and ensuring durability. RabbitMQ, however, does not provide built-in message persistence. Messages in RabbitMQ are transient by default, which means that they are stored in memory and may be lost if the broker crashes or restarts. However, RabbitMQ offers a persistence option for messages if needed, but it comes with some performance implications.

  4. Message Routing: ActiveMQ supports multiple message routing options, such as point-to-point, publish-subscribe, and request-reply patterns. It allows for flexible message routing based on topics and headers. RabbitMQ, on the other hand, primarily supports the publish-subscribe pattern, where a message is broadcasted to multiple consumers. It also provides a powerful feature called direct exchange for selective message routing based on routing keys.

  5. Scalability and Performance: ActiveMQ can handle a large number of connections and has shown excellent performance in throughput and latency. It supports clustering and can be scaled horizontally to handle high loads. RabbitMQ, on the other hand, is designed to be lightweight and performant with low-latency messaging. It focuses on providing high message throughput using efficient protocols like AMQP.

  6. Community and Support: ActiveMQ has been around for a longer time and has a large community of users, providing extensive documentation, tutorials, and online support. RabbitMQ, although relatively newer, also has a growing community of users and provides good documentation and support.

In summary, ActiveMQ and RabbitMQ differ in language support, ease of use, message persistence, message routing, scalability, and community support. These differences make them suitable for different use cases based on the specific requirements of the messaging system.

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Advice on RabbitMQ, ActiveMQ

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
ActiveMQ
ActiveMQ

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

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.

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
Protect your data & Balance your Load; Easy enterprise integration patterns; Flexible deployment
Statistics
GitHub Stars
13.2K
GitHub Stars
2.4K
GitHub Forks
4.0K
GitHub Forks
1.5K
Stacks
21.8K
Stacks
879
Followers
18.9K
Followers
1.3K
Votes
558
Votes
77
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
  • 18
    Easy to use
  • 14
    Open source
  • 13
    Efficient
  • 10
    JMS compliant
  • 6
    High Availability
Cons
  • 1
    ONLY Vertically Scalable
  • 1
    Difficult to scale
  • 1
    Low resilience to exceptions and interruptions
  • 1
    Support

What are some alternatives to RabbitMQ, ActiveMQ?

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.

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.

Apache Pulsar

Apache Pulsar

Apache Pulsar is a distributed messaging solution developed and released to open source at Yahoo. Pulsar supports both pub-sub messaging and queuing in a platform designed for performance, scalability, and ease of development and operation.

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