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  1. Stackups
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  4. Message Queue
  5. Google Cloud Messaging vs MQTT

Google Cloud Messaging vs MQTT

OverviewComparisonAlternatives

Overview

MQTT
MQTT
Stacks635
Followers577
Votes7
Google Cloud Messaging
Google Cloud Messaging
Stacks88
Followers247
Votes22

Google Cloud Messaging vs MQTT: What are the differences?

<h1>Key Differences Between Google Cloud Messaging and MQTT</h1>

<p>Google Cloud Messaging (GCM) and Message Queuing Telemetry Transport (MQTT) are both popular protocols used for communication in IoT and mobile applications. Here are the key differences between GCM and MQTT:</p>

<h2>1. Payload Limitation:</h2>
<p>GCM has a payload limit of 4KB, while MQTT allows for larger payloads, making it more suitable for applications requiring the transfer of larger chunks of data.</p>

<h2>2. Push vs Publish/Subscribe:</h2>
<p>GCM is principally a push notification service, where the server pushes messages to clients. On the other hand, MQTT follows a publish/subscribe model, enabling bi-directional communication between clients and servers.</p>

<h2>3. Reliability:</h2>
<p>GCM guarantees message delivery with its persistent connection to Google servers, ensuring reliable message delivery. MQTT, however, does not guarantee delivery as it relies on Quality of Service (QoS) levels chosen by the client.</p>

<h2>4. Message Queueing:</h2>
<p>Unlike GCM, MQTT uses a persistent message queue that stores messages until they are successfully delivered to clients, ensuring higher message reliability and durability.</p>

<h2>5. Security:</h2>
<p>GCM provides end-to-end encryption and secure transmission of data using Google's infrastructure, offering robust security measures. MQTT, on the other hand, may require additional security implementations to ensure data confidentiality.</p>

<h2>6. Connection Overhead:</h2>
<p>GCM has a lower connection overhead as it utilizes Google's infrastructure for message delivery, optimizing network resources. MQTT, being a lightweight protocol, may introduce slightly more connection overhead due to its direct client-to-broker communication.</p>

<h2>Summary:</h2>
<p>In summary, Google Cloud Messaging and MQTT differ in terms of payload limitation, communication model, reliability, message queueing, security measures, and connection overhead.</p>

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Detailed Comparison

MQTT
MQTT
Google Cloud Messaging
Google Cloud Messaging

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.

Google Cloud Messaging (GCM) is a free service that enables developers to send messages between servers and client apps. This includes downstream messages from servers to client apps, and upstream messages from client apps to servers.

-
Versatile Messaging Targets: Distribute messages to your client app in any of three ways — to single devices, to groups of devices, or to devices subscribed to topics.; Downstream Messaging: For purposes such as alerting users, chat messaging or kicking off background processing before the user opens the client app, GCM provides a reliable and battery-efficient connection between your server and devices.; Upstream Messaging: Send acknowledgments, chats, and other messages from devices back to your server over GCM’s reliable and battery-efficient connection channel.;
Statistics
Stacks
635
Stacks
88
Followers
577
Followers
247
Votes
7
Votes
22
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
  • 9
    Free
  • 6
    Scalable
  • 4
    Easy setup
  • 2
    Easy iOS setup
  • 1
    IOS Support
Cons
  • 1
    Reliability

What are some alternatives to MQTT, Google Cloud Messaging?

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.

OneSignal

OneSignal

OneSignal is a high volume push notification service for websites and mobile applications. OneSignal supports all major native and mobile platforms by providing dedicated SDKs for each platform, a RESTful server API, and a dashboard.

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.

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