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  5. MQTT vs nanomsg

MQTT vs nanomsg

OverviewComparisonAlternatives

Overview

MQTT
MQTT
Stacks635
Followers577
Votes7
nanomsg
nanomsg
Stacks10
Followers29
Votes0

MQTT vs nanomsg: What are the differences?

Introduction

In this article, we will discuss the key differences between MQTT and nanomsg.

  1. 1. Message Format: MQTT is a lightweight protocol that uses a simple binary message format. It is designed for efficient communication, with a header containing message type and flags. On the other hand, nanomsg is a socket library that provides several communication patterns, including publish-subscribe, request-reply, and pipeline. It supports more complex message structures and provides flexibility in message formatting.

  2. 2. QoS (Quality of Service): MQTT offers three levels of QoS: QoS 0 (at most once), QoS 1 (at least once), and QoS 2 (exactly once). These levels determine the reliability and delivery guarantees of messages. In contrast, nanomsg does not provide built-in QoS mechanisms. It focuses on fast and reliable message delivery within the chosen communication pattern, but lacks the fine-grained control over QoS provided by MQTT.

  3. 3. Implementation Language: MQTT has multiple implementations available in various programming languages, making it highly accessible and widely adopted. It has become the de facto standard for Internet of Things (IoT) communication. On the other hand, nanomsg is implemented in C and supports several language bindings, but it is not as widely adopted as MQTT.

  4. 4. Scalability: MQTT is designed to efficiently handle large-scale distributed systems with millions of connected devices. It supports lightweight clients and can easily scale to accommodate a high number of clients and messages. In contrast, nanomsg focuses on local communication within a single machine or a cluster of machines. It provides excellent performance for local tasks, but may not scale as well to large distributed systems.

  5. 5. Network Overhead: MQTT is designed to minimize network overhead and bandwidth usage. It uses a lightweight binary message format and includes optimizations like message compression and reduced protocol overhead. Nanomsg, while efficient in local communication, may have higher network overhead due to its more flexible message format and lack of specific mechanisms for minimizing network usage.

  6. 6. Protocol Support: MQTT is a well-established and standardized protocol that is widely supported by a variety of vendors and platforms. It has a large ecosystem of libraries, tools, and frameworks built around it. Nanomsg, while actively developed and maintained, may not have the same level of support and compatibility with different platforms and frameworks.

In summary, MQTT and nanomsg have key differences in terms of message format, QoS mechanisms, implementation language, scalability, network overhead, and protocol support. MQTT excels in lightweight communication, IoT applications, and large-scale distributed systems, while nanomsg provides more flexibility in message formatting and focuses on local communication within a machine or a cluster.

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Detailed Comparison

MQTT
MQTT
nanomsg
nanomsg

It was designed as an extremely lightweight publish/subscribe messaging transport. It is useful for connections with remote locations where a small code footprint is required and/or network bandwidth is at a premium.

It is a socket library that provides several common communication patterns. It aims to make the networking layer fast, scalable, and easy to use. Implemented in C, it works on a wide range of operating systems with no further dependencies.

-
Makes networking layer fast; Works on a wide range of operating systems
Statistics
Stacks
635
Stacks
10
Followers
577
Followers
29
Votes
7
Votes
0
Pros & Cons
Pros
  • 3
    Varying levels of Quality of Service to fit a range of
  • 2
    Lightweight with a relatively small data footprint
  • 2
    Very easy to configure and use with open source tools
Cons
  • 1
    Easy to configure in an unsecure manner
No community feedback yet
Integrations
No integrations available
Python
Python
JavaScript
JavaScript
C++
C++
.NET
.NET
Node.js
Node.js
Java
Java
PHP
PHP
Perl
Perl
Ruby
Ruby
Rust
Rust

What are some alternatives to MQTT, nanomsg?

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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