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

Amazon ElastiCache vs RabbitMQ

OverviewDecisionsComparisonAlternatives

Overview

Amazon ElastiCache
Amazon ElastiCache
Stacks1.3K
Followers1.0K
Votes151
RabbitMQ
RabbitMQ
Stacks21.8K
Followers18.9K
Votes558
GitHub Stars13.2K
Forks4.0K

Amazon ElastiCache vs RabbitMQ: What are the differences?

Introduction Amazon ElastiCache and RabbitMQ are both popular tools used in distributed computing and messaging systems. While they serve similar purposes, there are key differences that set them apart.

  1. Architecture:

    • Amazon ElastiCache is a fully-managed in-memory data store service that provides high-performance storage and retrieval capabilities. It is designed to improve the performance of web applications by caching frequently accessed data. ElastiCache supports the Memcached and Redis caching engines.
    • RabbitMQ, on the other hand, is an open-source message broker that implements the Advanced Message Queuing Protocol (AMQP). It enables applications to communicate asynchronously by sending and receiving messages. RabbitMQ supports various messaging patterns such as publish/subscribe, request/reply, and work queues.
  2. Functionality:

    • ElastiCache primarily focuses on caching and offers features like automatic data partitioning, data replication, and data expiration. It is suitable for use cases that involve caching frequently accessed data and reducing the load on databases or other data sources.
    • RabbitMQ, being a message broker, offers advanced queuing capabilities, including message routing, load balancing, and reliable message delivery. It is designed for scenarios that require reliable and scalable messaging between distributed systems or components.
  3. Scalability:

    • ElastiCache allows you to scale your cache capacity both vertically and horizontally. You can vertically scale ElastiCache nodes by increasing the memory capacity of individual cache nodes. Additionally, you can horizontally scale ElastiCache by adding or removing cache nodes based on the workload.
    • RabbitMQ is highly scalable as well. It supports the concept of queues, where messages are stored until they are consumed by subscribers. RabbitMQ can handle a large number of queues and allows for clustering, which enables distributing the load across multiple nodes for increased scalability.
  4. Data Persistence:

    • ElastiCache offers data persistence through Redis, allowing you to persist cache data on disk. This ensures data durability and allows data to be retained even if a cache node fails or is restarted.
    • RabbitMQ, by default, does not persist messages to disk. However, it provides options for durable queues and messages, allowing messages to survive even if the broker is restarted.
  5. Message Routing:

    • ElastiCache does not provide message routing capabilities. It is focused on caching data and does not have built-in functionality for routing messages between application components.
    • RabbitMQ offers a powerful message routing mechanism based on exchanges and bindings. Exchanges receive messages from publishers and route them to the appropriate queues based on predefined routing rules.
  6. Language Support:

    • ElastiCache and RabbitMQ support various programming languages, but RabbitMQ has broader language support. RabbitMQ provides official client libraries for popular programming languages like Java, Python, .NET, Ruby, and several others. ElastiCache has client libraries and SDKs for Java, Node.js, Python, .NET, PHP, and Go.

In Summary, Amazon ElastiCache is a caching service primarily focused on improving the performance of web applications, while RabbitMQ is a message broker designed for flexible and reliable messaging between distributed systems. ElastiCache is suited for caching frequently accessed data, while RabbitMQ excels in message queuing and routing. Both tools offer scalability options, although RabbitMQ has more extensive language support.

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Advice on Amazon ElastiCache, RabbitMQ

viradiya
viradiya

Apr 12, 2020

Needs adviceonAngularJSAngularJSASP.NET CoreASP.NET CoreMSSQLMSSQL

We are going to develop a microservices-based application. It consists of AngularJS, ASP.NET Core, and MSSQL.

We have 3 types of microservices. Emailservice, Filemanagementservice, Filevalidationservice

I am a beginner in microservices. But I have read about RabbitMQ, but come to know that there are Redis and Kafka also in the market. So, I want to know which is best.

933k views933k
Comments
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

Detailed Comparison

Amazon ElastiCache
Amazon ElastiCache
RabbitMQ
RabbitMQ

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.

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

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
Robust messaging for applications;Easy to use;Runs on all major operating systems;Supports a huge number of developer platforms;Open source and commercially supported
Statistics
GitHub Stars
-
GitHub Stars
13.2K
GitHub Forks
-
GitHub Forks
4.0K
Stacks
1.3K
Stacks
21.8K
Followers
1.0K
Followers
18.9K
Votes
151
Votes
558
Pros & Cons
Pros
  • 58
    Redis
  • 32
    High-performance
  • 26
    Backed by amazon
  • 21
    Memcached
  • 14
    Elastic
Pros
  • 235
    It's fast and it works with good metrics/monitoring
  • 80
    Ease of configuration
  • 60
    I like the admin interface
  • 52
    Easy to set-up and start with
  • 22
    Durable
Cons
  • 9
    Too complicated cluster/HA config and management
  • 6
    Needs Erlang runtime. Need ops good with Erlang runtime
  • 5
    Configuration must be done first, not by your code
  • 4
    Slow

What are some alternatives to Amazon ElastiCache, RabbitMQ?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

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.

Amazon SQS

Amazon SQS

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.

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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