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

Amazon SQS vs ZeroMQ

OverviewDecisionsComparisonAlternatives

Overview

Amazon SQS
Amazon SQS
Stacks2.8K
Followers2.0K
Votes171
ZeroMQ
ZeroMQ
Stacks258
Followers586
Votes71
GitHub Stars10.6K
Forks2.5K

Amazon SQS vs ZeroMQ: What are the differences?

Amazon SQS (Simple Queue Service) and ZeroMQ are two messaging systems used to facilitate communication between applications. Here are the key differences between Amazon SQS and ZeroMQ:

  1. Messaging Paradigm: Amazon SQS is a fully managed message queuing service provided by Amazon Web Services (AWS). It follows a message queue model, where messages are sent to and received from a queue. It ensures reliable and scalable message delivery and supports both FIFO (First-In-First-Out) and Standard queues. ZeroMQ, on the other hand, is a lightweight messaging library that follows a socket-based messaging paradigm. It provides a set of socket-like APIs that allow applications to send and receive messages directly between each other.

  2. Architecture and Deployment: Amazon SQS is a cloud-based service that is hosted and managed by AWS. It is designed to be highly available, durable, and scalable, making it suitable for distributed applications and microservices in the cloud. In contrast, ZeroMQ is a library that is integrated directly into applications. It is a low-level tool that allows developers to implement messaging patterns directly in their code. ZeroMQ can be used in various deployment scenarios, from local applications to distributed systems.

  3. Message Persistence and Durability: Amazon SQS guarantees message persistence, meaning messages are stored even if the consumer application is not currently available. This ensures that no messages are lost, and the messages can be processed at a later time. ZeroMQ, by default, does not provide built-in message persistence. If a message cannot be delivered immediately, it is discarded. However, developers can implement their own message persistence mechanisms using ZeroMQ's building blocks.

  4. Scalability and Throughput: Amazon SQS is designed for high scalability and can handle a large number of messages and consumers simultaneously. It automatically scales based on demand. ZeroMQ is lightweight and designed for low-latency communication within a single application or across a small set of interconnected applications. It can handle moderate message throughput.

  5. Protocol and Features: Amazon SQS provides a web service API, making it accessible to applications through HTTP or HTTPS protocols. It offers features like message filtering, dead-letter queues, and message attributes. ZeroMQ, being a library, can be integrated into applications using various language-specific bindings and supports a wide range of messaging patterns, including pub-sub, request-reply, and dealer-router patterns.

In summary, Amazon SQS is a fully managed, cloud-based message queuing service that provides high availability, scalability, and message durability, while ZeroMQ is a lightweight messaging library that allows direct communication between applications within a single environment or across a limited network.

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Advice on Amazon SQS, ZeroMQ

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
MITHIRIDI
MITHIRIDI

Software Engineer at LightMetrics

May 8, 2020

Needs adviceonAmazon SQSAmazon SQSAmazon MQAmazon 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 SQS
ZeroMQ
ZeroMQ

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.

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.

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.
Connect your code in any language, on any platform.;Carries messages across inproc, IPC, TCP, TPIC, multicast.;Smart patterns like pub-sub, push-pull, and router-dealer.;High-speed asynchronous I/O engines, in a tiny library.;Backed by a large and active open source community.;Supports every modern language and platform.;Build any architecture: centralized, distributed, small, or large.;Free software with full commercial support.
Statistics
GitHub Stars
-
GitHub Stars
10.6K
GitHub Forks
-
GitHub Forks
2.5K
Stacks
2.8K
Stacks
258
Followers
2.0K
Followers
586
Votes
171
Votes
71
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
    Difficult to configure
  • 2
    Proprietary
  • 2
    Has a max message size (currently 256K)
  • 1
    Has a maximum 15 minutes of delayed messages only
Pros
  • 23
    Fast
  • 20
    Lightweight
  • 11
    Transport agnostic
  • 7
    No broker required
  • 4
    Low latency
Cons
  • 5
    No message durability
  • 3
    Not a very reliable system - message delivery wise
  • 1
    M x N problem with M producers and N consumers

What are some alternatives to Amazon SQS, ZeroMQ?

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.

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.

Apache Pulsar

Apache Pulsar

Apache Pulsar is a distributed messaging solution developed and released to open source at Yahoo. Pulsar supports both pub-sub messaging and queuing in a platform designed for performance, scalability, and ease of development and operation.

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