Amazon SQS vs Sandglass

Overview

Amazon SQS

Stacks2.8K

Followers2.0K

Votes171

Sandglass

Stacks1

Followers6

Votes0

Amazon SQS vs Sandglass: What are the differences?

Amazon SQS: Fully managed message queuing service. 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; Sandglass: Distributed, scalable, persistent time-sorted message queue. A distributed, horizontally scalable, persistent, time ordered message queue. Developed to support asynchronous tasks and message scheduling which makes it suitable for usage as a task queue.

Amazon SQS and Sandglass can be primarily classified as "Message Queue" tools.

Some of the features offered by Amazon SQS are:

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.

On the other hand, Sandglass provides the following key features:

Horizontal scalability
Highly available
Persistent storage

Sandglass is an open source tool with 1.52K GitHub stars and 40 GitHub forks. Here's a link to Sandglass's open source repository on GitHub.

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Advice on Amazon SQS, Sandglass

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}|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

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	Sandglass
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.	A distributed, horizontally scalable, persistent, time ordered message queue. Developed to support asynchronous tasks and message scheduling which makes it suitable for usage as a task queue.
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.	Horizontal scalability; Highly available; Persistent storage; Time ordered; Multiple consumers per group for a partition; Produce message to be consumed in the future; Acknowledge/NotAcknowledge each message individually; Automatic redelivery and commit offset tracking; Language agnostic
Statistics
Stacks 2.8K	Stacks 1
Followers 2.0K	Followers 6
Votes 171	Votes 0
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	No community feedback yet
Integrations
No integrations available	Golang Java Python Node.js Ruby

What are some alternatives to Amazon SQS, Sandglass?

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.