IronMQ vs Kafka vs RabbitMQ

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IronMQ
IronMQ

32
36
+ 1
34
Kafka
Kafka

4.8K
4.2K
+ 1
484
RabbitMQ
RabbitMQ

5.6K
4.3K
+ 1
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What is 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.

What is Kafka?

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

What is RabbitMQ?

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
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Why do developers choose IronMQ?
Why do developers choose Kafka?
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What are some alternatives to IronMQ, Kafka, and RabbitMQ?
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.
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.
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
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.
MQTT
It was designed as an extremely lightweight publish/subscribe messaging transport. It is useful for connections with remote locations where a small code footprint is required and/or network bandwidth is at a premium.
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Decisions about IronMQ, Kafka, and RabbitMQ
James Cunningham
James Cunningham
Operations Engineer at Sentry · | 18 upvotes · 314.4K views
atSentrySentry
Celery
Celery
RabbitMQ
RabbitMQ
#MessageQueue

As Sentry runs throughout the day, there are about 50 different offline tasks that we execute—anything from “process this event, pretty please” to “send all of these cool people some emails.” There are some that we execute once a day and some that execute thousands per second.

Managing this variety requires a reliably high-throughput message-passing technology. We use Celery's RabbitMQ implementation, and we stumbled upon a great feature called Federation that allows us to partition our task queue across any number of RabbitMQ servers and gives us the confidence that, if any single server gets backlogged, others will pitch in and distribute some of the backlogged tasks to their consumers.

#MessageQueue

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Roman Bulgakov
Roman Bulgakov
Senior Back-End Developer, Software Architect at Chemondis GmbH · | 3 upvotes · 10.5K views
Kafka
Kafka

I use Kafka because it has almost infinite scaleability in terms of processing events (could be scaled to process hundreds of thousands of events), great monitoring (all sorts of metrics are exposed via JMX).

Downsides of using Kafka are: - you have to deal with Zookeeper - you have to implement advanced routing yourself (compared to RabbitMQ it has no advanced routing)

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Kafka
Kafka
RabbitMQ
RabbitMQ

The question for which Message Queue to use mentioned "availability, distributed, scalability, and monitoring". I don't think that this excludes many options already. I does not sound like you would take advantage of Kafka's strengths (replayability, based on an even sourcing architecture). You could pick one of the AMQP options.

I would recommend the RabbitMQ message broker, which not only implements the AMQP standard 0.9.1 (it can support 1.x or other protocols as well) but has also several very useful extensions built in. It ticks the boxes you mentioned and on top you will get a very flexible system, that allows you to build the architecture, pick the options and trade-offs that suite your case best.

For more information about RabbitMQ, please have a look at the linked markdown I assembled. The second half explains many configuration options. It also contains links to managed hosting and to libraries (though it is missing Python's - which should be Puka, I assume).

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Frédéric MARAND
Frédéric MARAND
Core Developer at OSInet · | 2 upvotes · 120.8K views
atOSInetOSInet
Beanstalkd
Beanstalkd
RabbitMQ
RabbitMQ
Kafka
Kafka

I used Kafka originally because it was mandated as part of the top-level IT requirements at a Fortune 500 client. What I found was that it was orders of magnitude more complex ...and powerful than my daily Beanstalkd , and far more flexible, resilient, and manageable than RabbitMQ.

So for any case where utmost flexibility and resilience are part of the deal, I would use Kafka again. But due to the complexities involved, for any time where this level of scalability is not required, I would probably just use Beanstalkd for its simplicity.

I tend to find RabbitMQ to be in an uncomfortable middle place between these two extremities.

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Michael Mota
Michael Mota
CEO & Founder at AlterEstate · | 4 upvotes · 77.2K views
atAlterEstateAlterEstate
Celery
Celery
RabbitMQ
RabbitMQ
Django
Django

Automations are what makes a CRM powerful. With Celery and RabbitMQ we've been able to make powerful automations that truly works for our clients. Such as for example, automatic daily reports, reminders for their activities, important notifications regarding their client activities and actions on the website and more.

We use Celery basically for everything that needs to be scheduled for the future, and using RabbitMQ as our Queue-broker is amazing since it fully integrates with Django and Celery storing on our database results of the tasks done so we can see if anything fails immediately.

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Reviews of IronMQ, Kafka, and RabbitMQ
Review ofRabbitMQRabbitMQ

I developed one of the largest queue based medical results delivery systems in the world, 18,000+ queues and still growing over a decade later all using MQSeries, later called Websphere MQ. When I left that company I started using RabbitMQ after doing some research on free offerings.. it works brilliantly and is incredibly flexible from small scale single instance use to large scale multi-server - multi-site architectures.

If you can think in queues then RabbitMQ should be a viable solution for integrating disparate systems.

Avatar of umuro
Co-Founder at Publitory
Review ofIronMQIronMQ

I deploy to Heroku. However, my applications require full linux applications that cannot be deployed to Heroku. I deploy them to Rackspace.

Then Heroku and Rackspace communicate over IronMQ. Problem solved.

How developers use IronMQ, Kafka, and RabbitMQ
Avatar of Pinterest
Pinterest uses KafkaKafka

http://media.tumblr.com/d319bd2624d20c8a81f77127d3c878d0/tumblr_inline_nanyv6GCKl1s1gqll.png

Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.

Avatar of Cloudify
Cloudify uses RabbitMQRabbitMQ

The poster child for scalable messaging systems, RabbitMQ has been used in countless large scale systems as the messaging backbone of any large cluster, and has proven itself time and again in many production settings.

Avatar of Chris Saylor
Chris Saylor uses RabbitMQRabbitMQ

Rabbit acts as our coordinator for all actions that happen during game time. All worker containers connect to rabbit in order to receive game events and emit their own events when applicable.

Avatar of Clarabridge Engage
Clarabridge Engage uses RabbitMQRabbitMQ

Used as central Message Broker; off-loading tasks to be executed asynchronous, used as communication tool between different microservices, used as tool to handle peaks in incoming data, etc.

Avatar of Analytical Informatics
Analytical Informatics uses RabbitMQRabbitMQ

RabbitMQ is the enterprise message bus for our platform, providing infrastructure for managing our ETL queues, real-time event notifications for applications, and audit logging.

Avatar of Packet
Packet uses RabbitMQRabbitMQ

RabbitMQ is an all purpose queuing service for our stack. We use it for user facing jobs as well as keeping track of behind the scenes jobs.

Avatar of Coolfront Technologies
Coolfront Technologies uses KafkaKafka

Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.

Avatar of ShareThis
ShareThis uses KafkaKafka

We are using Kafka as a message queue to process our widget logs.

Avatar of Christopher Davison
Christopher Davison uses KafkaKafka

Used for communications and triggering jobs across ETL systems

Avatar of theskyinflames
theskyinflames uses KafkaKafka

Used as a integration middleware by messaging interchanging.

Avatar of True Fiction Production AB
True Fiction Production AB uses IronMQIronMQ

Process queues

How much does IronMQ cost?
How much does Kafka cost?
How much does RabbitMQ cost?
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