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Hazelcast
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Hazelcast vs RabbitMQ: What are the differences?

Hazelcast: Clustering and highly scalable data distribution platform for Java. With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution; RabbitMQ: A messaging broker - an intermediary for messaging. RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Hazelcast and RabbitMQ are primarily classified as "In-Memory Databases" and "Message Queue" tools respectively.

Some of the features offered by Hazelcast are:

  • Distributed implementations of java.util.{Queue, Set, List, Map}
  • Distributed implementation of java.util.concurrent.locks.Lock
  • Distributed implementation of java.util.concurrent.ExecutorService

On the other hand, RabbitMQ provides the following key features:

  • Robust messaging for applications
  • Easy to use
  • Runs on all major operating systems

"High Availibility" is the top reason why over 4 developers like Hazelcast, while over 202 developers mention "It's fast and it works with good metrics/monitoring" as the leading cause for choosing RabbitMQ.

Hazelcast and RabbitMQ are both open source tools. It seems that RabbitMQ with 5.88K GitHub stars and 1.73K forks on GitHub has more adoption than Hazelcast with 3.15K GitHub stars and 1.15K GitHub forks.

According to the StackShare community, RabbitMQ has a broader approval, being mentioned in 921 company stacks & 532 developers stacks; compared to Hazelcast, which is listed in 25 company stacks and 15 developer stacks.

What is Hazelcast?

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

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 Hazelcast?
Why do developers choose RabbitMQ?

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    What are some alternatives to Hazelcast and RabbitMQ?
    Redis
    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
    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.
    Cassandra
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    Memcached
    Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
    Apache Ignite
    It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale
    See all alternatives
    Decisions about Hazelcast and RabbitMQ
    James Cunningham
    James Cunningham
    Operations Engineer at Sentry · | 18 upvotes · 144.2K 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
    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 · 95.9K 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 · 24.1K 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 Hazelcast 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 Hazelcast and RabbitMQ
    Avatar of Vital Labs, Inc.
    Vital Labs, Inc. uses HazelcastHazelcast

    HazelCast is the foundation for the distributed system that hosts our APIs and intelligent workflows. We wrap the core HazelCast functions in Clojure protocols to implement micro-services on top of a coherent, single-process instance per virtual node.

    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.

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