Amazon SQS, RabbitMQ, Redis & Zeplo Queuing Solutions: The Comparison

In a cloud computing environment, message queuing services provide applications and services with the ability to communicate. Through a cloud system or interface-managed message queue, you can integrate and collaborate physically distinct systems and applications on the fly.

In this article, we will compare different queuing solutions and discuss how difficult it is to set them up.

Amazon SQS

The Amazon Simple Queue Service (SQS) is a web service that gives users access to a message queue. This allows them to store messages while waiting for a computer to process them. Through SQS, developers can focus on differentiated tasks instead of managing and operating message-oriented middleware, which can be complex and time-consuming.

When using SQS, your software components can communicate at any volume without losing messages or having to rely on other services. The AWS Management Console, Command Line Interface, or SDK of your choice, and just three commands are all you need to get started with SQS.

Types of Amazon SQS

Amazon SQS offers two types of message queues:

  • Standard Queues
  • SQS FIFO Queues

Standard Queues: The standard queue offers maximum throughput, best-effort ordering, and at least once delivery.

SQS FIFO Queues: By design, SQS FIFO queues ensure that every message is processed exactly once and in the order in which it is sent.

How to Set Up Amazon SQS

The following steps must be completed before you can use Amazon SQS for the first time.

  • Create an AWS account
  • Create an IAM user
  • Get your access key ID and secret access key
  • Get ready to use the example code

Time required to Set Up

Amazon SQS takes approximately 14 days to set up.


It is based on the Erlang programming language. RabbitMQ is a popular open-source message queue. RabbitMQ is a lightweight messaging platform. Its website says that it can be deployed both on-premises and in the cloud, supporting several API protocols including AMQP, STOMP, MQTT, and HTTP. RabbitMQ can also run on different cloud environments and operating systems and support a lot of programming languages.

In a nutshell, it’s a middleware layer that allows the various services in your application to communicate without having to worry about message loss, while still maintaining a high quality of service (QoS). Additionally, it enables efficient message routing, allowing applications to be decoupled to a great extent.

How RabbitMQ Works?

This is how it would work with RabbitMQ following the example of a web application that allows users to submit information and then generates a PDF:

  • The user uploads their data to the web application for use in generating the PDF.
  • A message is issued by the web application (the producer) to RabbitMQ titled “Process PDF”. The user’s name and email address are also contained in the message.
  • Messages are received and routed through an exchange (within RabbitMQ), which receives and routes the message to the right queue.
  • The message is retrieved from the queue and the PDF processing worker begins working on it.

Time required to Set Up

There are often many tunable parameters in data services like RabbitMQ. For development, some practices and configurations are useful, but aren’t necessarily suitable for production. A single configuration does not fit all use cases.

Thus, prior to launching production, system configuration and “day two operations” activities such as upgrades should be assessed. It is pertinent to mention here that RabbitMQ takes approx. 1 week to completely function.


It is an open-source in-memory database and cache that is written in C, open-source under a BSD license, and designed for speed. Redis stands for “REmote DIctionary Server”.

As a result of its data structure server status, Redis is often called a programming language data structure server as its core data types resemble those found in programming languages such as strings, lists, dictionaries, sets, and sorted sets. Additionally, the app provides a wide variety of data structures and features for approximate counting, geo-location, and stream processing.

A default setting for Redis is to store data in memory and persist it on a periodic basis. Because Redis persists its data to disk, it can be used in many applications as both a database and a cache. The Redis cache can be configured to eject older data as new data is received by the client, if it is full. However, it will return an error to the client when full. The main constraint on the use of memory is the size of the available memory.

How to Set Up Redis?

Redis is available on different operating systems including Linux, MacOS, and Windows and from Source. You can install Redis from its official website Redis.

Time Required to Set Up and Maintain Redis

Redis is configured within a time period ranging from 2 days to 14 days. It depends on the operating system which is ready to be configured or set up. It takes more time to set up in Linux and MacOS as compared to Windows.


Zeplo is one of the best message queuing solutions which doesn’t run the code itself, but instead sends a HTTPS request to your endpoint at the exact time it needs to run and can automatically or manually retry it if it fails.

Why choose Zeplo over Redis, RabbitMQ or AWS SQS

Zeplo is the fastest message queuing solution as compared to Amazon SQS, Redis and RabbitMQ which take several days to completely configure and set up. On the other hand Zeplo takes only 5 minutes to completely configure and set up.

Features of Zeplo

It has following salient features which makes this queueing solution unique and more advanced than others:

  • Delay & Schedule: Schedule a job to run after a given time, or at regular intervals (CRON, time or RRULE).
  • Auto Retry: Specify how many times to retry the request before failing, with customizable backoff.
  • Tracing: Every job is traced, including all headers and body for enhanced debugging.
  • Rate Limit: Auto-handles rate limit response headers, automatically retrying after the requested backoff.
  • Manual Retry: Fix and reprocess failed records in the console to ensure your jobs are always completed.
  • Bulk Push: Push multiple jobs to the queue at once, ensuring transaction safe queueing.
  • Webhook notifications: Get notifications on the state of messages in the queue


We conclude that Redis memory size and AWS permissions are annoying and they also take several days to get fully functional and configured. With Zeplo you don’t need to manage job state, queues, or workers and it takes just 5 minutes to deliver. You already have a HTTPS API, so creating a second interface and API for every service and method to make it asynchronous adds duplication and complexity. The consumer service no longer needs to know whether it will be called async or sync. It’s the publishing/calling service that gets to decide.

Sign up at to experience the HTTP message queueing solution.

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