MQTT Broker Comparison – MQTTRoute vs Mosquitto

MQTT Broker Comparison – MQTTRoute vs Mosquitto

MQTT is one of the most widely adopted protocols today in the IoT Arena. There are a lot of MQTT Brokers available for your solution implementation.  Choosing the right one that fits your criteria makes your project more than 50% complete. Developers should evaluate and lay out distinct quality aspects of all available Brokers to make a right choice. In an article earlier this year, we wrote about How to choose a perfect MQTT server for your implementation. Bevywise MQTTRoute is a commercial MQTT server built using C and python. Similarly,  Mosquitto is one of the fastest open source broker built on C. This article gives a high level overview of the MQTT Broker comparison between MQTTRoute and Mosquitto.

MQTT Compliance

Both Mosquitto and Bevywise are built as per MQTT protocol specification like publish message format, command messages, QoS(Quality of Service), retain, Wild card topics and error handling etc.

MQTT Security

Security of a broker is largely determined by the user configuration and only to a lesser extent by the broker’s security features. These include authentication and authorization mechanisms, as well as encryption support. In that case both MQTT Brokers support high level device authentication & TLS/SSL MQTT security. With the recent update, Bevywise MQTTRoute comes with the custom authentication functionality to execute centralized identity management / authentication.

High Availability

MQTT Broker must be highly available in order to never miss / loss any MQTT data. It should be up and running without any failure and hence you need MQTT clusters for it. In that case, Bevywise MQTTRoute supports clustering which can be used to set up 99.99% high availability MQTT cluster. As of now Mosquitto doesn’t handle high availability in it.

MQTT Data Persistence

IOT / IIoT is not about communication. It is about storing data for future analysis and decision-making. Mosquitto by default process all the message communication in memory. There is an option to store data of subscription into a file (mosquitto.db). But this file cannot be used outside the application. However, MQTTRoute comes with a default option to store data into MySQL, SQLite & PostgreSQL.  We recommend MySQL for deployments and the application you are building can also query the database in parallel. In addition MQTTRoute allows you to write data into ElasticSearch, MongoDB or any other storage using the plugin system built into the it.

MQTT Dashboard

One of the critical issue in the MQTT Implementation today is that the manager applications are built over data received by an MQTT client that subscribe to #. But, this is not the right as the meta information of the data is lost. So this mandates the need for the Broker to be integral part of the application. Keeping this in mind, we have built the UI into the MQTT Broker. We have built a comprehensive MQTT Dashboard as part of the MQTTRoute as well as the Platform. Also, MQTTRoute supports creating multiple dashboards with some pre-built widgets intended to provide better visualization of data. However, Mosquitto does not have any User interface as the data persistence itself is not available. There are some third party User interfaces which are built as a client.


Above all, The default web interface of the MQTTRoute can be customized as needed. The Product can be white labelled. Mosquitto as a open source MQTT broker can be customized to a larger extent. But the customization is more on the C layer for the Mosquitto and all the building blocks over it need to be recreated. Bevywise MQTTRoute on the other hand allows customization at the appliation layer. Some of the customization includes changing the User interface, advanced visualization, transforming data before storage. Moreover, Bevywise MQTTRoute is not just a Broker, it is a complete IoT application suite with the extendable custom hooks. The custom hooks include Custom UI server, Custom scheduler, Custom data store & Custom authentication.


Data Hooks, REST API and ML/AI Integration are the three major integration end points of the Bevywise MQTTRoute. MQTTRoute makes a huge leap ahead when you want to build an application over the Mosquitto. With the support of AI/ML integration you can add a ML algorithm into MQTTRoute to automate your machine learning process. Other than REST API’s, Bevywise MQTT server can be customizable to integrate with other MQTT based tools like Google pub/sub, Redis, tableau, modbus and more. Besides that, the cost and the effort spent on customization will be very minimal when compared to Mosquitto.

MQTT Broker Performance Comparison 

Performance of MQTT Broker depends on two main metrics one is the maximum sustainable throughput and the other is the average latency. The first metric is the maximum sustainable throughput at which the Broker is able to process all communicated messages. In terms of sustainability, Mosquitto is built on C and Bevywise MQTTRoute is built on a combination of C & Python for easy extendability and performance. Mosquitto is the fastest MQTT server available today when run as just a message broker. Bevywise MQTTRoute has a throughput at par with the Mosquitto.

The next one is the average latency from publisher to subscriber in a given scenario. Short latencies are important for many IoT applications, where live monitoring of data is desired. In terms of latency, both has a has lower latency/message delivery time across all QOSes. And also, MQTTRoute has the exposure of better latency (less round the trip time) than Mosquitto in QOS 0. To know more on MQTT Broker performance, have a look at the performance comparison study done by University of Szeged, Hungary.

Support & Consulting

MQTTRoute comes with a FREE Support where in we do consluting for your implementation while you will not be getting these supports on the Open Source Brokers. We also provide FREE community support for FREE users. Read more about our support policy.

MQTT Broker comparison Table





MQTT, Web socket

MQTT, WebSocket

Visualization of Data

In built Dashboard with details of Devices level. Manage devices with send command, create Rules via UI. Multiple dashboard & widgets support.


thrid party plugin



device level Authentication,

Custom Authentication


device level authentication

Inbuilt Storage Options

MySQL / SQLite / PostgreSQL

Allows Third-party application to read.

Store data in-memory & File

Only for Internal purpose

Extendable data Storage

Extension based Storage using Custom_storage option. Prebuilt connectors available in Github.

third party plugins for Storage


Windows, Windows server, Linux, Mac and Raspberry Pi

Linux, Mac, Windows and BSD

Rule Engine

YES. Custom Rules can be added from the User Interface.


Error Log

YES. Time Out errors , Authentication, Packet errors are deducted and shown on the UI.

Yes, Enabled at the conf file and show in the Terminal


Yes. Option to customize to any language




No. One used as a single cluster

SaaS based

Yes. IoT Platform supports SaaS based Scalable architecture



Developed and will be available soon


Complete MQTT Standard Support




REST API , Data Plugins, ML/AI

Only DATA Plugins

Docker Support






Open source



Built on

C / Python language

C language

MQTT version

Current support MQTT 3.1.1 and MQTT 5 coming soon

Current support MQTT 3.1.1 and MQTT 5 coming soon


24×7 live support via Telephone, Whattsapp, Email.

Forum support


The overall MQTT Broker comparison between MQTTRoute & Mosquitto will help you choose the best one for your IoT implementation.

You can try the Bevywise MQTTRoute by downloading it FREE now. The new version of MQTT server, MQTTRoute 3.1 is available to support integration of central identity access management (IAM).

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Feel free to write to support for any questions / suggestions.

Bevywise IoT for Education

Bevywise IoT for Education

IoT is the future connectivity, Are we enabling the classrooms of today to embrace and adapt with the technology!”.

Industries of today like manufacturing, logistics and more have adapted the IOT technology transformation to build custom implementation and powerful analytical applications using AI/ML integration with IOT application framework. So are the education industry ready for the challenge to groom the students for the IOT revolution?

No problem, Bevywise IOT for education is here to guide you all the way.

Package with Benefits

Bevywise facilitates the intuitive understanding of deterministic concepts with the IoT Educational pack. For instance, with Bevywise Enterprise MQTT Broker setup in the premise, students and teachers can manipulate joint deterministic distributions to perform inference. Integrate AI/ML and configure dynamic messages into the MQTTRoute. Students are granted access to write custom code, deploy AI/ML algorithms with the high extendable python hooks to customize UI with dynamic data and to visualize on own widgets and graphs to make decisions. Bevywise IOT platform provides custom MQTT clients for custom implementation for all resources in the institutions.

The available powerful Bevywise IOT Simulator allows to share interactive models with your audience, without having to install any software on their computer. It is configured to specific network and helps students to test and create templates, connect multiple devices to the Manager application. Students will be able to emulate real scenarios without the real devices.

More Affordable IoT Educational Pack

Recognizing the limited budgets available for academic, we offer and released a specially-priced version of our Bevywise IoT for Education, which is specifically designed and only available to accredited academic institutions.

The FREE Student version helps individual students learn by themselves with setting up the products on their laptop. We have added more value into the Research Edition and  University Edition at an affordable cost.

For more details on how you can utilize these packages for your Universities, talk to an expert or refer to the IOT for Education Page.

IoT Success Stories – MQTT Broker – FAB Controls

IoT Success Stories – MQTT Broker – FAB Controls

Monitoring or measuring serves to be an effective step to move towards proactive decisions. Because, monitoring is necessary to be attentive to any anomaly, no matter how small, to keep close watch on components. Besides that, you will be able to act in consequence of any situation. One of our customers, FAB Controls is an IoT solution provider  in the United Kingdom who provide IoT solutions to the lighting and energy industries. EmMonIT is their exclusive emergency lighting control solution. Their emergency lighting control device effectively monitors lighting continuously to ensure it is fully operational.This is one of our  IoT Success stories of MQTTRoute implementation.

Foolproof Emergency lighting

EmMonIT constantly checks status for emergency lighting. Besides that,the data is collected securely and it can be accessible anywhere at anytime. Therefore, any faults identified can be notified to the relevant parties. The continuous monitoring provides a virtual foolproof way to take actionable decisions to address any issues.

To know more about Emergency Monitor IT visit FAB Controls website.

Role of MQTTRoute in Lighting control

MQTTRoute plays a vital role in their emergency monitoring solution. MQTTRoute acts a central broker and therefore it collects data from lighting control devices and pushes it to Google pubsub to create simple and real-time visualization of data. As a result,The MQTTRoute implementation addresses their need and provides them a complete solution. This is one of our  IoT Success stories.

For more details and queries on MQTTRoute, you can visit our website.

Download the MQTTRoute, the complete MQTT Application Framework now.

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We will be happy to hear your requirements to provide a complete solution. Let us talk now.

Transforming MQTT Broker into IoT Application Framework

Transforming MQTT Broker into IoT Application Framework

Eat your own dog food is one of the most heard words from Sridhar Vembu when I was working for Zoho.   This is a practice done while we were creating Zoho Writer and Zoho document management system and is practiced today as well. It is nothing but using the software created by your company for your customers for their own internal purpose. This is one of the most simple and powerful ways to understand the problems faced by your customer.  It helps in identifying enhancements you can make on your software.  We  transformed the MQTT Broker into an IoT Application Framework practicing the same.  Over the past few months, we were building products for manufacturing execution system above our MQTTRoute

Data Collection & Storage

Against all the hosted IoT Code vendors like Google, AWS, Azure and the other MQTT Brokers like HiveMQ , Mosquitto, from the initial days, we wanted to build something more than just being a broker.  Message brokers just  transacts messages between interested machines & devices. One of the most not so scalable solution we inferred in market is building manager application behind an MQTT client. MQTTRoute had options to store data into any database which can be processed by the manager application. We had multiple hooks to receive data and manage your edge devices by sending commands to the edge devices.  The MQTT Broker came with an user interface ( a more technical one ) to view and manage devices.

What we learnt?

We have been seeing some of our customers directly querying our database or integrating it with the Google PubSub or Redis or Tableau for further processing and visualizing data. This was happening in spite of our user interface and device management options like send command to devices and the rules engine. However,  without any flaws, MQTTRoute is able to do the functions intended.

We started building the Daily production monitor for manufacturing industry (discrete process) as part of one of  MES initiatives. The development cycle helped us understand that the broker was doing its core right. But it does not 100% cover the requirements for building up a complete industry 4.0 application.

MQTTRoute 2.0 – The complete IoT Application Framework

We have been working hard to ensure that the complete internet of things application including user interface customization, data aggregation & analysis, event data comparison with the processed data.  All custom implementation can be done using the additional hooks. These hooks as of now are python based.  We will roll out the same, in a week’s time. We believe the new IoT application framework will help building and managing the industrial IoT applications faster and much easier within a single process.

Feel free to write to us if you have any specific need that needs to be addressed for your Industry Implementation.

Voice Control Devices using Alexa & Googlehome

Voice Control Devices using Alexa & Googlehome

Human race has been tied to actions by touch for a prolonged period. Touch is something bound to the extend to which you can stretch your arms and body. Sound and Vision goes a long way beyond horizons. The advent of image processing techniques largely influenced the addition of visual recognition to the machines. Along with the Industry 4.0 and the current home automation trend, a lot of innovation is happening over Sound. We can control everything around us with voice using voice hearing robots like Apple Siri, Amazon Alexa, Microsofts’ Cortana, Google Home / Assistant.

Home Automation leads the Voice Race

Voice and IoT go hand in hand, freeing users from being tied down by screens, data and physical inputs. Voice commands have arguably become one of the greatest and quickest way to control home devices. Just give a voice command from anywhere to automate your device at home. Turning on the air-conditioning before actually stepping inside the home. Turning off the lights when no one is in the room and controlling the brightness of light for energy efficiency. Adding connectivity to fire safety devices can provide house owners with the ability to monitor remotely and even send alerts to neighbors in the event of emergency. When you develop smart home for your customers, you need to get the IoT platform that already has voice integration. Bevywise IoT platform is one such platform that comes out of the box with integration for Google Home / Assist & Amazon Alexa.

Voice control in Industries

Industries today has not started embracing the voice as a primary medium. The world has been fed up with typing for a long time. It is time to rethink the integration of voice into the manufacturing echo system. Sirens has been used for a long time to mark time and alarms for emergency. However, we believe more reporting in the future will happen using voice than the need for texual reading and writing. Wherever you go the lighting and temperature controls all perform in concert to optimize your comfort based on your pre-determined personal indictors. In order to check the growth of a particular year, you can use voice control and this will create a graph show-casting the year’s growth in click through rates. This will eventually replace going through files manually.

We can strengthen the security of the industry instead of swiping cards. In addition, The proper functioning of your machines can be monitored periodically with a voice command anywhere, anytime. In order to start the meeting, just give a voice command to your voice assistant, it will turn on the video conference system and dial into the conference hall. The automation creates intelligent processes for monitoring and decision-making and to economize the supply chain and production.

Voice control in Health Care

With the advent of technology in medical care, we are generating a lot of medical records in the format of images and textual PDF. We are storing medical records in a highly secure environment. These data are highly analysed today to make very predictive solutions. One of the major integration we forsee for the medical care for the physicians are the integration of voice. We believe that physicians will be using more and more voice to pull out the medical records of patients and draw conclusions. This will be highly useful during surgical operations. Pulling records using voice will highly save time than manual entry of data on the screens.

The technology of voice recognization has come and long way so that the tools and devices today can understand variations in voice and also identify the owner to act accordingly.

You can connect your devices to the IoT Platform today by signing up to a fresh account.

Refer to the help documentation for how to integrate voice using Amazon Alexa and Google Home.