Top 5 Open Source Message Queue (MQ) Software In 2021

Message queue (MQ) software is used to handle asynchronous communication. The queue provides asynchronous protocols to allow data communications within a system.

Open Source Message Queue (MQ) Software In 2021
Top 5 Open Source Message Queue (MQ) Software In 2021

Overview

An open source message queue (MQ) software is used to handle a variety of tasks asynchronously. It is used to enable process-related asynchronous communication within IT systems with queue messaging system. Asynchronous communication means that the endpoints that are producing and consuming messages interact with only the queuing service, not with each other. Message queue mq provides asynchronous protocols to communicate remotely and at different times between senders and receivers. Messages consist of requests, replies, or alerts depending on the sender’s need.

Open source message broker is an important part of software systems to send or receive messages in text and other formats. Message queuing service allows software applications to communicate and flow between various services within a system. Message queue software provides temporary message storage when the destination program is busy on other tasks. Internally, message broker software use a queue system to send or receive all messages and work on the principle of LIFO (Last-In, First-Out). Messages placed onto the queue are stored in lightweight buffer and then run in the background.

The following blog article will help you to focus on the best message queue software options in the year 2021.

  • Apache Kafka
  • RabbitMQ
  • Celery
  • Nsq
  • Redisson
  • Other Messaging Queue Software Options to Consider
  • Final Thoughts

1. Apache Kafka — Robust Queue Broker

Kafka  is an open source messaging system and a robust queue broker. It is distributed event streaming platform and has the ability to handle a high volume of messages. Kafka messages are stored on the disk and it allows you to send messages from one point to another seamlessly. Messages are replicated within the whole Kafka cluster to prevent unwanted operations from happening like any data loss. Kafka messaging platform built to handle real-time event streaming, pipe-lining and replaying of data for fast, scalable operations.

Apache Kafka distributed message queue software is used by thousands of companies for high performance data pipelines and its integration with Apache Storm and Spark. Kafka offers high performance as compared to message and queue brokers like ActiveMQ and RabbitMQ etc. Apache Kafka is an alternative to a variety of enterprise messaging systems. It was built as an internal messaging system developed by Linked-in to handle 1.4 trillion messages in a day. It is a best and suitable platform for the implementation of Queues since it boosts performance by using sequential disk I/O operations. It is also a perfect choice for big data use cases because it can achieve high throughput with limited number of resources, i.e millions of messages per second.

2. RabbitMQ — Robust Messaging for Applications

RabbitMQ is the most widely deployed and popular open source best message broker software — an intermediary for messaging. It’s written in Erlang programming language and is backed by the Pivotal Software Foundation. It gives your applications a common platform and a safe place to send and receive messages. It’s features include performance, reliability, high availability, clustering and federation etc. RabbitMQ ships with an easy to use management UI that allows you to monitor and control your message broker.

RabbitMQ message broker or queue manager can be downloaded from the official website for all of the major operating systems i.e Linux, Windows, and macOS. It is recommended to use RabbitMQ plugins to ease the workload of message brokers and to expand it’s functions. The most important RabbitMQ plugin is the management plugin and you have to activate it manually. RabbitMQ management plugin helps users to operate RabbitMQ using it through a Graphical User Interface. It helps in viewing different statistics related to messaging and also keeping an overview of all of the operations with data happening in queues.

3. Celery — Distributed Task Queue

Celery is an open source, flexible, and reliable distributed message queue system to process vast amounts of messages. It is a task queue with focus on real-time processing while it also supports task scheduling. Celery is licensed under the BSD License. Celery has a simple asynchronous process queue or job queue which is based on distributed message passing. The execution units or process tasks are executed concurrently on a single or more worker nodes using multiprocessing, eventlet or gevent. Celery tasks run asynchronously in the background or synchronously.

Celery is written using Python but the protocol can be implemented in any language. Celery is used in production systems like for Instagram, to process millions of tasks every day. It can also work with other programming languages using webhooks. There is a PHP client, Go client, a Node.js client and a Ruby-Client called RCelery. Celery is an open source message queue with 17.6K GitHub stars and 4K GitHub forks.

4. Nsq — Realtime Distributed Messaging

NSQ is an open source and modern real-time distributed memory best message queue designed to operate at scale. It is written in Go language and handles billions of messages per day on a large scale. NSQ has distributed message and decentralized topology structure. It’s characteristics are of no single point of failure. It enables fault tolerance and high availability coupled with the efficient delivery of messages.

NSQ is mature product, easy to configure and has excellent performance. All configuration and deployment parameters are specified on the command line and compiled binaries have no runtime dependencies. NSQ messages data format can be JSON, MsgPack, Protocol Buffers, or anything else for maximum flexibility. It has official Go and Python libraries out of the box as well as many other client libraries. NSQ has three main necessary components nsqd, nsqlookupd, and nsqadmin. NSQ is an open source tool with 19.9K GitHub stars and 2.6K GitHub forks.

5. Redisson — Distributed Java Service

Redisson is the most advanced and easiest Redis Java client with features of In-Memory data grid. It is very simple, easy to learn and message queue monitoring tool thus you don’t need to know any Redis commands to start configuring with Redisson. It is required Redis based objects, collections, locks, synchronizers and services for distributed applications on Java platform. Task services on Java might be run in parallel with Redis based distributed implementations with ExecutorService and ScheduledExecutorService.

Redisson has support for Redis configurations, manage Redis services support, Engine, distributed Java objects, distributed Java locks and synchronizers, distributed Java services, distributed Java collections, integration with Java frameworks, support for SSL and OSGi, supported codecs, Redis based Java message broker for Pub/Sub and Stream messaging. The open source Redisson project 16.9K GitHub stars and 4.1K GitHub forks.

Other Messaging Queue Software Options to Consider:

  • Apache ActiveMQ is powerfull open source messaging and integration patterns server.
  • Bull for handling distributed jobs and messages in NodeJS.
  • NATS Messaging is an open-source messaging system.
  • Qutrunk Software as a service messaging platform.

Final Thoughts:

We have discussed most popular message brokers and task queue libraries spanning many programming languages and implementations. There are a lot of open source and closed source messaging platforms and new are on their way to solve the problems that engineers face with scheduling. So, it is really necessary that you understand the pros and cons of different tools and then pick up one that suitable for your needs. When you have a cloud-agnostic messaging queue service with a user-friendly dashboard and excellent security, you can make your business application more efficient than ever. In our upcoming tutorials, we’ll discuss more interesting topics of open source messaging platforms.

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