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  5. Azure Service Bus vs MQTT

Azure Service Bus vs MQTT

OverviewDecisionsComparisonAlternatives

Overview

MQTT
MQTT
Stacks635
Followers577
Votes7
Azure Service Bus
Azure Service Bus
Stacks553
Followers536
Votes7

Azure Service Bus vs MQTT: What are the differences?

Introduction

Azure Service Bus and MQTT are both messaging protocols used for communication between devices and applications. While they serve a similar purpose, there are several key differences between the two.

  1. Scalability and Flexibility: Azure Service Bus is a cloud-based messaging service provided by Microsoft Azure, offering highly scalable and flexible messaging capabilities. It allows for asynchronous communication between different applications and services. MQTT, on the other hand, is a lightweight and efficient messaging protocol designed for constrained devices and low-bandwidth networks. It is particularly suitable for Internet of Things (IoT) scenarios where resources are limited.

  2. Protocol Design: Azure Service Bus uses a request-response model where the sender and receiver need not be online simultaneously. It provides features like message queues and topics, allowing for reliable and durable messaging. MQTT, on the other hand, follows a publish-subscribe model where clients can publish messages to topics and subscribers can receive messages from those topics. It is designed for efficient and low-latency communication.

  3. Reliability and Persistence: Azure Service Bus ensures message durability and persistence by storing messages in its message queues or topics until they are consumed by the receivers. In case of network disruptions or receiver unavailability, the messages are stored and delivered when the connection is restored. MQTT, on the other hand, relies on the Quality of Service (QoS) levels specified during message publication. It supports three levels of QoS, including at most once, at least once, and exactly once delivery. The QoS level chosen affects the reliability and persistence of the messages.

  4. Authentication and Security: Azure Service Bus provides various authentication mechanisms to ensure secure communication, including shared access signatures, Azure Active Directory, and Transport Layer Security (TLS) encryption. It also supports message-level security using message encryption. MQTT, on the other hand, primarily relies on Transport Layer Security (TLS) encryption for secure communication. It also provides support for username/password-based authentication and client certificates.

  5. Language and Platform Support: Azure Service Bus provides SDKs and libraries for different programming languages such as .NET, Java, Python, etc. It also integrates well with other Azure services like Azure Functions, Azure Logic Apps, etc. MQTT, on the other hand, has MQTT client libraries available for a wide range of programming languages and platforms, making it highly portable and compatible with diverse systems.

  6. Level of Overhead: While Azure Service Bus provides rich messaging features and capabilities, it comes with a certain level of complexity and overhead due to the cloud infrastructure it relies on. MQTT, being a lightweight and efficient protocol, has lower overhead in terms of bandwidth and processing requirements, making it suitable for resource-constrained devices and networks.

In Summary, Azure Service Bus and MQTT differ in terms of scalability, protocol design, reliability, authentication, language and platform support, and overhead. Azure Service Bus is a cloud-based messaging service offering scalability and flexibility, while MQTT is a lightweight protocol designed for constrained devices and low-bandwidth networks.

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Advice on MQTT, Azure Service Bus

André
André

Technology Manager at GS1 Portugal - Codipor

Jul 30, 2020

Needs adviceon.NET Core.NET Core

Hello dear developers, our company is starting a new project for a new Web App, and we are currently designing the Architecture (we will be using .NET Core). We want to embark on something new, so we are thinking about migrating from a monolithic perspective to a microservices perspective. We wish to containerize those microservices and make them independent from each other. Is it the best way for microservices to communicate with each other via ESB, or is there a new way of doing this? Maybe complementing with an API Gateway? Can you recommend something else different than the two tools I provided?

We want something good for Cost/Benefit; performance should be high too (but not the primary constraint).

Thank you very much in advance :)

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Comments

Detailed Comparison

MQTT
MQTT
Azure Service Bus
Azure Service Bus

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 cloud messaging system for connecting apps and devices across public and private clouds. You can depend on it when you need highly-reliable cloud messaging service between applications and services, even when one or more is offline.

Statistics
Stacks
635
Stacks
553
Followers
577
Followers
536
Votes
7
Votes
7
Pros & Cons
Pros
  • 3
    Varying levels of Quality of Service to fit a range of
  • 2
    Very easy to configure and use with open source tools
  • 2
    Lightweight with a relatively small data footprint
Cons
  • 1
    Easy to configure in an unsecure manner
Pros
  • 4
    Easy Integration with .Net
  • 2
    Cloud Native
  • 1
    Use while high messaging need
Cons
  • 1
    Skills can only be used in Azure - vendor lock-in
  • 1
    Lacking in JMS support
  • 1
    Observability of messages in the queue is lacking
  • 1
    Limited features in Basic tier

What are some alternatives to MQTT, Azure Service Bus?

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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