Overview

Amazon SQS

Stacks2.3K

Followers2.0K

Votes171

Amazon MQ

Stacks54

Followers325

Votes12

Amazon MQ vs Amazon SQS: What are the differences?

Introduction

In this article, we will explore the key differences between Amazon MQ and Amazon SQS in the context of their messaging systems.

MQ Broker vs. Message Queue: Amazon MQ is a fully managed message broker service that supports the Apache ActiveMQ and RabbitMQ messaging protocols. It provides a powerful broker-based messaging system that allows for advanced features like message filtering, prioritization, and redelivery policies. On the other hand, Amazon SQS is a managed message queuing service that decouples the components of a distributed application by allowing them to communicate asynchronously. Unlike Amazon MQ, it does not provide a full-fledged broker system and relies on simple message queues instead.
Protocol Support: Amazon MQ supports both the Apache ActiveMQ and RabbitMQ protocols, which have been widely used in enterprise messaging scenarios. It provides compatibility with existing applications built using these protocols, allowing for a smooth transition to the managed service. In contrast, Amazon SQS uses a proprietary protocol and does not support the ActiveMQ or RabbitMQ protocols directly. However, it does provide SDKs and client libraries for different programming languages to simplify the integration process.
Message Persistence: Amazon MQ allows you to choose the level of message persistence based on your use case requirements. It supports both durable and non-durable messaging, where durable messages are stored on disk to ensure reliability even in the event of a system failure. On the other hand, Amazon SQS ensures message durability by storing messages redundantly across multiple availability zones of the region, eliminating the risk of message loss.
Message Delivery: Amazon MQ supports both message push and message pull models. In the push model, the messaging system actively delivers messages to consumers, while in the pull model, consumers actively poll the broker to retrieve messages. This flexibility allows you to design your applications based on the specific requirements. In contrast, Amazon SQS exclusively uses a message pull model, where consumers actively retrieve messages from the queue. The pull model is more suitable for scenarios where the consumer needs to control the rate of message processing.
Throughput and Scalability: Amazon MQ provides greater throughput and scalability compared to Amazon SQS. It supports a higher number of messages per second and concurrent connections, making it suitable for high-volume, high-throughput applications. On the other hand, Amazon SQS is designed for high elasticity, automatically scaling up or down based on the incoming load. It can handle large bursts of traffic without any manual intervention, making it a good choice for applications with unpredictable workloads.
Deployment Complexity: Amazon MQ requires more configuration and management compared to Amazon SQS. As a fully managed message broker service, Amazon MQ requires you to provision and manage the underlying broker instances, including capacity planning, scaling, and installation of updates. In contrast, Amazon SQS abstracts away the infrastructure management, allowing you to focus solely on the messaging logic.

In summary, Amazon MQ provides a robust message broker system with support for multiple protocols, advanced features, and high throughput. On the other hand, Amazon SQS offers a simpler message queuing system with seamless scalability and reliability, ideal for decoupling components in distributed applications.

Advice on Amazon SQS, Amazon MQ

Pulkit

Software Engineer

Oct 30, 2020

Needs adviceon

Django

Amazon SQS

RabbitMQ

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

Software engineer at Digital Science

Sep 24, 2020

Needs adviceon

ZeroMQ

RabbitMQ

Amazon 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 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

MITHIRIDI

Software Engineer at LightMetrics

May 8, 2020

Needs adviceon

Amazon SQS

Amazon MQ

I want to schedule a message. Amazon SQS provides a delay of 15 minutes, but I want it in some hours.

Example: Let's say a Message1 is consumed by a consumer A but somehow it failed inside the consumer. I would want to put it in a queue and retry after 4hrs. Can I do this in Amazon MQ? I have seen in some Amazon MQ videos saying scheduling messages can be done. But, I'm not sure how.

303k views303k

Comments

Detailed Comparison

Amazon SQS	Amazon MQ
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.	Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud.
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 2.3K	Stacks 54
Followers 2.0K	Followers 325
Votes 171	Votes 12
Pros & Cons
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	Pros 7 Supports low IQ developers 3 Supports existing protocols (JMS, NMS, AMQP, STOMP, …) 2 Easy to migrate existing messaging service Cons 4 Slow AF
Integrations
No integrations available	AWS IAM Amazon CloudWatch ActiveMQ

What are some alternatives to Amazon SQS, Amazon MQ?

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 gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

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 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

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

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

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 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

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

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.