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  1. Stackups
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  3. Background Jobs
  4. Message Queue
  5. Amazon SQS vs Azure Storage

Amazon SQS vs Azure Storage

OverviewDecisionsComparisonAlternatives

Overview

Amazon SQS
Amazon SQS
Stacks2.8K
Followers2.0K
Votes171
Azure Storage
Azure Storage
Stacks1.3K
Followers787
Votes52

Amazon SQS vs Azure Storage: What are the differences?

Introduction

In this article, we will discuss the key differences between Amazon Simple Queue Service (Amazon SQS) and Azure Storage. Both Amazon SQS and Azure Storage are popular cloud-based messaging services that provide reliable and scalable solutions for managing queues and storing data. However, there are several important differences between the two platforms that developers need to consider when choosing the right messaging service for their applications.

  1. Message Delivery Model: Amazon SQS follows a "polling" model, where consumers retrieve messages by repeatedly polling the SQS queue to check for new messages. Azure Storage, on the other hand, uses a "push" model, where consumers are notified through event-driven mechanisms such as Azure Blob Storage triggers or Azure Queue Storage queues.

  2. Message Retention Period: In Amazon SQS, the maximum retention period for a message is 14 days. After this period, the message will be automatically deleted from the queue. Azure Storage provides a similar retention period of up to 7 days for messages in both Azure Queue Storage and Azure Service Bus.

  3. Message Ordering: Amazon SQS guarantees that messages are delivered in the same order they are sent within a single Message Group. Azure Storage, specifically Azure Queue Storage, does not provide inherent support for ordering messages and developers need to implement their own mechanisms for maintaining message order if required.

  4. Visibility Timeout: When a consumer retrieves a message from an Amazon SQS queue, the message becomes temporarily "invisible" to other consumers while the first consumer processes it. This timeout period can be configured by the developer. Azure Storage provides a similar visibility timeout mechanism called "message invisibility timeout" in Azure Queue Storage.

  5. Functionality: Amazon SQS offers a broader range of messaging capabilities, including both standard and FIFO (first-in-first-out) queues, dead-letter queues, and message retention policies. Azure Storage provides Azure Queue Storage, which is a simple FIFO queue, and Azure Service Bus, which provides more advanced messaging features such as pub/sub messaging, message sessions, and dead-lettering.

  6. Availability Zones: Amazon SQS allows developers to choose the availability zone(s) for their queues to ensure high availability and fault tolerance. Azure Storage provides a similar concept of "storage accounts" that are automatically replicated across multiple availability zones in a region for increased availability.

In summary, the key differences between Amazon SQS and Azure Storage include the message delivery model, message retention period, message ordering, visibility timeout mechanism, functionality (including the availability of advanced features), and the concept of availability zones. These differences should be considered based on application requirements when choosing a messaging service.

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Advice on Amazon SQS, Azure Storage

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
Azure Storage
Azure Storage

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.

Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to 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.
Blobs, Tables, Queues, and Files;Highly scalable;Durable & highly available;Premium Storage;Designed for developers
Statistics
Stacks
2.8K
Stacks
1.3K
Followers
2.0K
Followers
787
Votes
171
Votes
52
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
  • 24
    All-in-one storage solution
  • 15
    Pay only for data used regardless of disk size
  • 9
    Shared drive mapping
  • 2
    Cheapest hot and cloud storage
  • 2
    Cost-effective
Cons
  • 2
    Direct support is not provided by Azure storage
Integrations
No integrations available
Microsoft Azure
Microsoft Azure

What are some alternatives to Amazon SQS, Azure Storage?

Amazon S3

Amazon S3

Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web

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.

Amazon EBS

Amazon EBS

Amazon EBS volumes are network-attached, and persist independently from the life of an instance. Amazon EBS provides highly available, highly reliable, predictable storage volumes that can be attached to a running Amazon EC2 instance and exposed as a device within the instance. Amazon EBS is particularly suited for applications that require a database, file system, or access to raw block level storage.

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.

Google Cloud Storage

Google Cloud Storage

Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure.

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.

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