Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Kafka
Kafka

4.3K
3.6K
+ 1
476
NSQ
NSQ

82
114
+ 1
127
RabbitMQ
RabbitMQ

5.1K
3.8K
+ 1
466

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 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.

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.
Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Why do developers choose Kafka?
Why do developers choose NSQ?
Why do developers choose RabbitMQ?

Sign up to add, upvote and see more prosMake informed product decisions

What companies use Kafka?
What companies use NSQ?
What companies use RabbitMQ?

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Kafka?
What tools integrate with NSQ?
What tools integrate with RabbitMQ?
    No integrations found

    Sign up to get full access to all the tool integrationsMake informed product decisions

    What are some alternatives to Kafka, NSQ, and RabbitMQ?
    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.
    Amazon Kinesis
    Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    Akka
    Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM.
    Apache Storm
    Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
    See all alternatives
    Decisions about Kafka, NSQ, and RabbitMQ
    James Cunningham
    James Cunningham
    Operations Engineer at Sentry · | 18 upvotes · 214.9K 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

    See more
    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)

    See more
    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).

    See more
    Frédéric MARAND
    Frédéric MARAND
    Core Developer at OSInet · | 2 upvotes · 103.2K 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.

    See more
    Michael Mota
    Michael Mota
    CEO & Founder at AlterEstate · | 4 upvotes · 51.6K 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.

    See more
    Interest over time
    Reviews of Kafka, NSQ, 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.

    How developers use Kafka, NSQ, 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 InsideSales.com
    InsideSales.com uses NSQNSQ

    The built-in Gamification that comes with our Playbooks application uses NSQ for work queues and microservice communication.

    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.

    How much does Kafka cost?
    How much does NSQ cost?
    How much does RabbitMQ cost?
    Pricing unavailable
    Pricing unavailable
    Pricing unavailable
    News about NSQ
    More news
    News about RabbitMQ
    More news