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  1. Stackups
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  4. Message Queue
  5. Hazelcast vs RabbitMQ

Hazelcast vs RabbitMQ

OverviewDecisionsComparisonAlternatives

Overview

RabbitMQ
RabbitMQ
Stacks21.8K
Followers18.9K
Votes558
GitHub Stars13.2K
Forks4.0K
Hazelcast
Hazelcast
Stacks427
Followers474
Votes59
GitHub Stars6.4K
Forks1.9K

Hazelcast vs RabbitMQ: What are the differences?

Introduction

Hazelcast and RabbitMQ are two popular technologies used for different purposes. While Hazelcast is an in-memory data grid and distributed computing platform, RabbitMQ is a message broker that enables various components of an application to communicate with each other. Although they have some similarities, there are significant differences between the two.

  1. Data Storage and Processing: Hazelcast is primarily used for storing and processing data in a distributed manner across multiple nodes. It provides a highly available and fault-tolerant solution for storing and retrieving data. On the other hand, RabbitMQ focuses on message queuing and asynchronous communication between different components of an application.

  2. Messaging Patterns: Hazelcast supports publish/subscribe messaging, where a message published to a topic is received by multiple subscribers. RabbitMQ, on the other hand, supports various messaging patterns such as point-to-point, publish/subscribe, request/reply, and routing. This flexibility allows RabbitMQ to handle different communication scenarios efficiently.

  3. Protocol Support: Hazelcast provides a proprietary binary protocol that allows clients and servers to communicate efficiently. It also supports various serializers, such as Java Serialization and JSON, for storing complex data types. In contrast, RabbitMQ uses the AMQP (Advanced Message Queuing Protocol) standard, which is a widely accepted protocol for message-oriented middleware. This makes RabbitMQ compatible with a wide range of clients and platforms.

  4. Message Durability: Hazelcast, being an in-memory data grid, provides fast and efficient data storage but may lose data in case of node failures. It can be configured to replicate data across multiple nodes for better durability. RabbitMQ, on the other hand, ensures message durability by persisting messages on disk and storing them in queues until they are consumed by consumers.

  5. Integration with Other Technologies: Hazelcast can be easily integrated with other technologies like databases, caching frameworks, and other distributed systems. It provides APIs and connectors to interact with different systems seamlessly. RabbitMQ also offers seamless integration with various technologies and frameworks, with support for multiple client libraries in different programming languages.

  6. Message Routing and Queuing: Hazelcast does not provide built-in support for advanced message routing and queuing mechanisms. It primarily focuses on data storage and processing. In contrast, RabbitMQ provides features like message routing based on headers, message attributes, and routing keys. It also supports priority queues, dead letter exchanges, and message expiration mechanisms.

In summary, Hazelcast is a distributed computing platform mainly used for high-performance data storage and processing, while RabbitMQ is a message broker focused on providing reliable and efficient message queuing and communication between different components of an application.

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Advice on RabbitMQ, Hazelcast

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
Meili
Meili

Software engineer at Digital Science

Sep 24, 2020

Needs adviceonZeroMQZeroMQRabbitMQRabbitMQAmazon SQSAmazon SQS

Hi, we are in a ZMQ set up in a push/pull pattern, and we currently start to have more traffic and cases that the service is unavailable or stuck. We want to:

  • Not loose messages in services outages
  • Safely restart service without losing messages (@{ZeroMQ}|tool:1064| seems to need to close the socket in the receiver before restart manually)

Do you have experience with this setup with ZeroMQ? Would you suggest RabbitMQ or Amazon SQS (we are in AWS setup) instead? Something else?

Thank you for your time

500k views500k
Comments

Detailed Comparison

RabbitMQ
RabbitMQ
Hazelcast
Hazelcast

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

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.

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
Distributed implementations of java.util.{Queue, Set, List, Map};Distributed implementation of java.util.concurrent.locks.Lock;Distributed implementation of java.util.concurrent.ExecutorService;Distributed MultiMap for one-to-many relationships;Distributed Topic for publish/subscribe messaging;Synchronous (write-through) and asynchronous (write-behind) persistence;Transaction support;Socket level encryption support for secure clusters;Second level cache provider for Hibernate;Monitoring and management of the cluster via JMX;Dynamic HTTP session clustering;Support for cluster info and membership events;Dynamic discovery, scaling, partitioning with backups and fail-over
Statistics
GitHub Stars
13.2K
GitHub Stars
6.4K
GitHub Forks
4.0K
GitHub Forks
1.9K
Stacks
21.8K
Stacks
427
Followers
18.9K
Followers
474
Votes
558
Votes
59
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
  • 11
    High Availibility
  • 6
    Distributed Locking
  • 6
    Distributed compute
  • 5
    Sharding
  • 4
    Load balancing
Cons
  • 4
    License needed for SSL
Integrations
No integrations available
Java
Java
Spring
Spring

What are some alternatives to RabbitMQ, Hazelcast?

Redis

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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.

Aerospike

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

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.

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