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  1. Stackups
  2. Utilities
  3. Caching
  4. Managed Memcache
  5. Amazon ElastiCache vs Amazon SQS

Amazon ElastiCache vs Amazon SQS

OverviewDecisionsComparisonAlternatives

Overview

Amazon ElastiCache
Amazon ElastiCache
Stacks1.3K
Followers1.0K
Votes151
Amazon SQS
Amazon SQS
Stacks2.8K
Followers2.0K
Votes171

Amazon ElastiCache vs Amazon SQS: What are the differences?

Introduction

In this article, we will discuss the key differences between Amazon ElastiCache and Amazon SQS. Both of these services are provided by Amazon Web Services (AWS) and are widely used for different purposes in cloud computing environments.

  1. Elasticity and Scalability: One key difference between Amazon ElastiCache and Amazon SQS is their primary focus. ElastiCache is designed as an in-memory data store service that provides high-performance caching. It is built to seamlessly scale up and down to handle varying workloads efficiently. On the other hand, Amazon SQS is a managed message queuing service that enables decoupling of distributed systems and enhances fault tolerance. It is designed to provide reliable message delivery with scalable and durable message queues.

  2. Data Persistence and Durability: ElastiCache stores data in-memory, which provides extremely fast access times. However, this also means that the data is not inherently persistent, and any data lost due to a cache node failure or reboot is not recoverable. In contrast, Amazon SQS stores messages in a highly durable and reliable manner, ensuring that messages are not lost even if due to system failures or accidental deletion. SQS messages are automatically replicated across multiple availability zones for enhanced durability.

  3. Protocols and Supported Data Types: ElastiCache is compatible with the popular Redis and Memcached protocols, providing support for key-value data stores and facilitating seamless integration with existing applications that use these protocols. Amazon SQS, on the other hand, follows a simple messaging protocol and provides a platform-independent way of exchanging messages between application components. It supports a variety of data types, including strings, numbers, and binary data.

  4. Message Delivery and Order: In Amazon ElastiCache, the data access is typically immediate, as it is stored in-memory within the cache. This allows for extremely low latency and high throughput data retrieval. However, in Amazon SQS, the order of message delivery is not guaranteed, and multiple consumers can receive messages concurrently from the same queue. This makes SQS an ideal choice for applications that require parallel processing or asynchronous communication between components.

  5. Managed Service and Monitoring: ElastiCache is a fully-managed service, meaning that AWS takes care of the underlying infrastructure, patching, and backups. It also provides various monitoring metrics and logs, enabling users to monitor the performance and usage of their cache clusters. Amazon SQS is also a managed service, handling the operational aspects of message queuing. It offers diagnostic and monitoring features, such as CloudWatch metrics and CloudTrail logs, for tracking queue activity and performance.

  6. Use Cases and Prerequisites: ElastiCache is commonly used for improving the performance of applications by caching frequently accessed data, reducing the load on databases, and improving overall response times. It is often used in scenarios that require low-latency data retrieval, such as real-time applications, session stores, and gaming leaderboards. Amazon SQS, on the other hand, is used for building distributed systems and decoupling components to enable fault-tolerant and highly scalable architectures. It is widely used in scenarios involving microservices, event-driven architectures, and background job processing.

In Summary, Amazon ElastiCache and Amazon SQS have key differences in terms of their focus, data persistence, supported protocols, message delivery, management, and use cases. ElastiCache prioritizes high-performance caching with in-memory data storage, while SQS focuses on reliable message queuing with durable message persistence.

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Advice on Amazon ElastiCache, Amazon SQS

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 ElastiCache
Amazon ElastiCache
Amazon SQS
Amazon SQS

ElastiCache improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache supports Memcached and Redis.

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.

Support for two engines: Memcached and Redis;Ease of management via the AWS Management Console. With a few clicks you can configure and launch instances for the engine you wish to use.;Compatibility with the specific engine protocol. This means most of the client libraries will work with the respective engines they were built for - no additional changes or tweaking required.;Detailed monitoring statistics for the engine nodes at no extra cost via Amazon CloudWatch;Pay only for the resources you consume based on node hours used
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
1.3K
Stacks
2.8K
Followers
1.0K
Followers
2.0K
Votes
151
Votes
171
Pros & Cons
Pros
  • 58
    Redis
  • 32
    High-performance
  • 26
    Backed by amazon
  • 21
    Memcached
  • 14
    Elastic
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

What are some alternatives to Amazon ElastiCache, Amazon SQS?

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.

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.

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.

MemCachier

MemCachier

MemCachier provides an easy and powerful managed caching solution for all your performance and scalability needs. It works with the ubiquitous memcache protocol so your favourite language and framework already supports it.

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.

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