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  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Message Queue
  5. Amazon SQS vs CloudAMQP

Amazon SQS vs CloudAMQP

OverviewDecisionsComparisonAlternatives

Overview

CloudAMQP
CloudAMQP
Stacks62
Followers84
Votes7
Amazon SQS
Amazon SQS
Stacks2.8K
Followers2.0K
Votes171

Amazon SQS vs CloudAMQP: What are the differences?

Introduction

Amazon Simple Queue Service (SQS) and CloudAMQP are both message queuing services that are commonly used in cloud computing applications. While they share some similarities in terms of their core functionalities, there are several key differences between these two services. In this article, we will explore these differences in detail.

  1. Messaging Model: The messaging model in Amazon SQS is based on the "at least once" delivery semantics, which means that a message can be delivered to a consumer multiple times but guarantees that it will be delivered at least once. On the other hand, CloudAMQP relies on the "at most once" delivery semantics, which ensures that a message will be delivered once or not at all. This fundamental difference in delivery semantics affects how developers design their applications to handle duplicate or missing messages.

  2. Management Console: Amazon SQS provides a comprehensive web-based management console that allows users to easily create, configure, and monitor their queues. It offers a user-friendly interface with built-in charts and metrics for queue visibility. In contrast, CloudAMQP does not have its own management console but relies on the RabbitMQ management API. Users need to use external tools or develop custom applications to interact with CloudAMQP queues.

  3. Pricing Structure: Amazon SQS has a pay-as-you-go pricing model based on the number of requests and the data transfered. It offers different pricing tiers depending on the region and provides a free tier for low-volume usage. CloudAMQP, on the other hand, follows a usage-based pricing model where users are billed for the number of connections, the rate of messages, and the amount of data stored. It does not offer a free tier but provides a 30-day free trial.

  4. Integration with Cloud Services: As part of the Amazon Web Services (AWS) ecosystem, Amazon SQS seamlessly integrates with other AWS services such as AWS Lambda, AWS Elastic Beanstalk, and AWS CloudFormation. This allows developers to build scalable and resilient applications by leveraging the full suite of AWS offerings. CloudAMQP also provides integrations with various cloud platforms and services, but it may require additional configuration and setup compared to using standard AWS services.

  5. Load Balancing and Scaling: Amazon SQS automatically handles load balancing and scaling for message processing. It distributes messages across multiple servers, ensuring high availability and fault tolerance. CloudAMQP, on the other hand, relies on the underlying RabbitMQ infrastructure for load balancing and scaling. Users need to manually configure and manage RabbitMQ clusters to achieve high availability and scalability.

  6. Advanced Features: Amazon SQS offers additional advanced features such as dead-letter queues, which allow you to isolate and troubleshoot messages that cannot be processed successfully. It also provides long-polling capabilities for efficient message retrieval and delayed message delivery for scheduling tasks. While CloudAMQP supports most of the core RabbitMQ features, some advanced features may require additional configuration or customization.

In Summary, Amazon SQS and CloudAMQP differ in their messaging model, management console, pricing structure, integration with cloud services, load balancing and scaling mechanisms, and advanced features. These differences should be considered when choosing the appropriate message queuing service for your cloud-based application.

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Advice on CloudAMQP, Amazon SQS

Pulkit
Pulkit

Software Engineer

Oct 30, 2020

Needs adviceonDjangoDjangoAmazon SQSAmazon SQSRabbitMQRabbitMQ

Hi! I am creating a scraping system in Django, which involves long running tasks between 1 minute & 1 Day. As I am new to Message Brokers and Task Queues, I need advice on which architecture to use for my system. ( Amazon SQS, RabbitMQ, or Celery). The system should be autoscalable using Kubernetes(K8) based on the number of pending tasks in the queue.

474k views474k
Comments
Meili
Meili

Software engineer at Digital Science

Sep 24, 2020

Needs adviceonZeroMQZeroMQRabbitMQRabbitMQAmazon SQSAmazon SQS

Hi, we are in a ZMQ set up in a push/pull pattern, and we currently start to have more traffic and cases that the service is unavailable or stuck. We want to:

  • Not loose messages in services outages
  • Safely restart service without losing messages (@{ZeroMQ}|tool:1064| seems to need to close the socket in the receiver before restart manually)

Do you have experience with this setup with ZeroMQ? Would you suggest RabbitMQ or Amazon SQS (we are in AWS setup) instead? Something else?

Thank you for your time

500k views500k
Comments
Mickael
Mickael

DevOps Engineer at Rookout

Mar 1, 2020

Decided

In addition to being a lot cheaper, Google Cloud Pub/Sub allowed us to not worry about maintaining any more infrastructure that needed.

We moved from a self-hosted RabbitMQ over to CloudAMQP and decided that since we use GCP anyway, why not try their managed PubSub?

It is one of the better decisions that we made, and we can just focus about building more important stuff!

472k views472k
Comments

Detailed Comparison

CloudAMQP
CloudAMQP
Amazon SQS
Amazon SQS

Fully managed, highly available RabbitMQ servers and clusters, on all major compute platforms.

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.

Support - 24/7 support, via email, chat and phone.; Real time metrics and alarms - Get notified in advanced when your queues are growing faster than you're consuming them, when you're servers are over loaded etc. and take action before it becomes a problem.; Auto-healing - Our monitoring systems automatically detects and fixes a lot of problems such as kernel bugs, auto-restarts, RabbitMQ/Erlang version upgrades etc.; Metrics - Of course the default RabbitMQ interface is available, which gives you great inspection capabilities of your queues and message throughput, but we also gives you CPU, RAM and disk graphs to help you monitor the health and resource consumption of your clusters.;
A queue can be created in any region.;The message payload can contain up to 256KB of text in any format. Each 64KB ‘chunk’ of payload is billed as 1 request. For example, a single API call with a 256KB payload will be billed as four requests.;Messages can be sent, received or deleted in batches of up to 10 messages or 256KB. Batches cost the same amount as single messages, meaning SQS can be even more cost effective for customers that use batching.;Long polling reduces extraneous polling to help you minimize cost while receiving new messages as quickly as possible. When your queue is empty, long-poll requests wait up to 20 seconds for the next message to arrive. Long poll requests cost the same amount as regular requests.;Messages can be retained in queues for up to 14 days.;Messages can be sent and read simultaneously.;Developers can get started with Amazon SQS by using only five APIs: CreateQueue, SendMessage, ReceiveMessage, ChangeMessageVisibility, and DeleteMessage. Additional APIs are available to provide advanced functionality.
Statistics
Stacks
62
Stacks
2.8K
Followers
84
Followers
2.0K
Votes
7
Votes
171
Pros & Cons
Pros
  • 4
    Some of the best customer support you'll ever find
  • 3
    Easy to provision
Pros
  • 62
    Easy to use, reliable
  • 40
    Low cost
  • 28
    Simple
  • 14
    Doesn't need to maintain it
  • 8
    It is Serverless
Cons
  • 2
    Has a max message size (currently 256K)
  • 2
    Difficult to configure
  • 2
    Proprietary
  • 1
    Has a maximum 15 minutes of delayed messages only
Integrations
AppHarbor
AppHarbor
Google Compute Engine
Google Compute Engine
Heroku
Heroku
DigitalOcean
DigitalOcean
Amazon EC2
Amazon EC2
Red Hat OpenShift
Red Hat OpenShift
SoftLayer
SoftLayer
dotCloud
dotCloud
Pivotal Web Services (PWS)
Pivotal Web Services (PWS)
AppFog
AppFog
No integrations available

What are some alternatives to CloudAMQP, Amazon SQS?

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.

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.

IronMQ

IronMQ

An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.

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