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  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Message Queue
  5. Mosquitto vs RSMQ

Mosquitto vs RSMQ

OverviewComparisonAlternatives

Overview

RSMQ
RSMQ
Stacks4
Followers87
Votes6
GitHub Stars1.8K
Forks120
Mosquitto
Mosquitto
Stacks136
Followers306
Votes14

Mosquitto vs RSMQ: What are the differences?

## Key Differences Between Mosquitto and RSMQ

1. **Protocol Support**: Mosquitto primarily focuses on MQTT protocol for efficient messaging between machines, whereas RSMQ implements a simple Redis-based message queue protocol for communication.
   
2. **Persistence Mechanism**: Mosquitto stores message data on disk to ensure message persistence even during server restarts, whereas RSMQ relies on Redis for message storage, providing a highly scalable and in-memory storage mechanism.
   
3. **Scalability**: Mosquitto is capable of handling thousands of clients and messages efficiently, making it suitable for large-scale deployments, while RSMQ is designed to be a lightweight queue system, ideal for applications where simplicity and speed are prioritized over handling massive loads.
   
4. **Message Priority**: Mosquitto does not natively support message prioritization, treating all messages equally, whereas RSMQ allows developers to set priority levels for messages, ensuring critical tasks are processed first.
   
5. **Monitoring and Management**: Mosquitto provides extensive monitoring and management capabilities through built-in tools and plugins, enabling administrators to track system performance and troubleshoot issues effectively. In contrast, RSMQ lacks advanced monitoring features, requiring developers to rely on external tools for in-depth insights.
   
6. **Community Support**: Mosquitto benefits from a large and active community of developers and users, offering a wide range of resources, plugins, and extensions for customization and integration. On the other hand, RSMQ, being a more specialized solution, has a smaller but dedicated community focused on enhancing its core functionalities.

In Summary, Mosquitto and RSMQ differ in protocol support, persistence mechanism, scalability, message priority, monitoring capabilities, and community support, catering to distinct messaging and queuing requirements in various applications.

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CLI (Node.js)
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Detailed Comparison

RSMQ
RSMQ
Mosquitto
Mosquitto

tl;dr: If you run a Redis server and currently use Amazon SQS or a similar message queue you might as well use this fast little replacement. Using a shared Redis server multiple Node.js processes can send / receive messages.

It is lightweight and is suitable for use on all devices from low power single board computers to full servers.. The MQTT protocol provides a lightweight method of carrying out messaging using a publish/subscribe model. This makes it suitable for Internet of Things messaging such as with low power sensors or mobile devices such as phones, embedded computers or microcontrollers.

Lightweight: Just Redis and ~500 lines of javascript.;Guaranteed delivery of a message to exactly one recipient within a messages visibility timeout.;Received messages that are not deleted will reappear after the visibility timeout.;Test coverage;Optional RESTful interface via rest-rsmq
-
Statistics
GitHub Stars
1.8K
GitHub Stars
-
GitHub Forks
120
GitHub Forks
-
Stacks
4
Stacks
136
Followers
87
Followers
306
Votes
6
Votes
14
Pros & Cons
Pros
  • 2
    Simple, does one thing well
  • 1
    Written in Coffeescript
  • 1
    Backed by Redis
  • 1
    Written in TypeScript
  • 1
    Comes with a visibility timeout feature similar to AWS
Pros
  • 10
    Simple and light
  • 4
    Performance
Integrations
Redis
Redis
No integrations available

What are some alternatives to RSMQ, Mosquitto?

Kafka

Kafka

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

RabbitMQ

RabbitMQ

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

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.

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.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

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