Faktory vs RabbitMQ

Overview

RabbitMQ

Stacks21.8K

Followers18.9K

Votes558

GitHub Stars13.2K

Forks4.0K

Faktory

Stacks7

Followers27

Votes3

GitHub Stars6.0K

Forks236

Faktory vs RabbitMQ: What are the differences?

Introduction

When comparing Faktory and RabbitMQ, it is essential to be aware of their key differences to make an informed decision on which messaging system best suits your needs.

1. Protocol Support: Faktory primarily uses its proprietary network protocol based on MessagePack, while RabbitMQ supports standard protocols such as AMQP, MQTT, and STOMP.

2. Ease of Use: Faktory is designed to be simple to set up and configure, with a focus on developer-friendly features like a modern REST API. In contrast, RabbitMQ has more configuration options and can be more complex to manage for certain use cases.

3. Message Reliability: RabbitMQ offers more advanced features for message reliability, like publisher confirms, acknowledgments, and persistent messages. On the other hand, Faktory may be more suitable for scenarios where message durability is not a top priority.

4. Scalability: RabbitMQ is known for its robust clustering support, making it easier to scale horizontally and handle higher message volumes. Faktory, while still capable of scaling, might not offer the same level of scalability out of the box.

5. Community and Ecosystem: RabbitMQ boasts a larger and more established user community, along with extensive documentation and plugins. Faktory, being relatively newer, might have a smaller support network and a more limited ecosystem of integrations and tools.

6. Use Cases: RabbitMQ is often preferred for enterprise-grade applications with high message throughput and complex routing requirements. Faktory, on the other hand, might be better suited for smaller projects or environments with a focus on simplicity and ease of use.

In Summary, understanding the key differences between Faktory and RabbitMQ in areas such as protocol support, ease of use, message reliability, scalability, community support, and ideal use cases is crucial for choosing the right messaging system for your specific requirements.

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Advice on RabbitMQ, Faktory

viradiya

Apr 12, 2020

Needs adviceon

AngularJS

ASP.NET Core

MSSQL

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

André

Technology Manager at GS1 Portugal - Codipor

Jul 30, 2020

Needs adviceon

.NET Core

Hello dear developers, our company is starting a new project for a new Web App, and we are currently designing the Architecture (we will be using .NET Core). We want to embark on something new, so we are thinking about migrating from a monolithic perspective to a microservices perspective. We wish to containerize those microservices and make them independent from each other. Is it the best way for microservices to communicate with each other via ESB, or is there a new way of doing this? Maybe complementing with an API Gateway? Can you recommend something else different than the two tools I provided?

We want something good for Cost/Benefit; performance should be high too (but not the primary constraint).

Thank you very much in advance :)

461k views461k

Comments

mediafinger

Feb 13, 2019

Reviewon

Kafka

RabbitMQ

The question for which Message Queue to use mentioned "availability, distributed, scalability, and monitoring". I don't think that this excludes many options already. I does not sound like you would take advantage of Kafka's strengths (replayability, based on an even sourcing architecture). You could pick one of the AMQP options.

I would recommend the RabbitMQ message broker, which not only implements the AMQP standard 0.9.1 (it can support 1.x or other protocols as well) but has also several very useful extensions built in. It ticks the boxes you mentioned and on top you will get a very flexible system, that allows you to build the architecture, pick the options and trade-offs that suite your case best.

For more information about RabbitMQ, please have a look at the linked markdown I assembled. The second half explains many configuration options. It also contains links to managed hosting and to libraries (though it is missing Python's - which should be Puka, I assume).

159k views159k

Comments

Detailed Comparison

RabbitMQ	Faktory
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.	Redis -> Sidekiq == Faktory -> Faktory. Faktory is a server daemon which provides a simple API to produce and consume background jobs. Jobs are a small JSON hash with a few mandatory keys.
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 13.2K	GitHub Stars 6.0K
GitHub Forks 4.0K	GitHub Forks 236
Stacks 21.8K	Stacks 7
Followers 18.9K	Followers 27
Votes 558	Votes 3
Pros & Cons
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	Pros 2 Worker language agnostic 1 Simple service API
Integrations
No integrations available	Node.js Ruby Python Golang Elixir PHP Java JavaScript

What are some alternatives to RabbitMQ, Faktory?

Kafka

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

Sidekiq

Sidekiq uses threads to handle many jobs at the same time in the same process. It does not require Rails but will integrate tightly with Rails 3/4 to make background processing dead simple.

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

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 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.

Beanstalkd

Beanstalks's interface is generic, but was originally designed for reducing the latency of page views in high-volume web applications by running time-consuming tasks asynchronously.

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.

Related Comparisons

Faktory vs RabbitMQ: What are the differences?

Introduction

When comparing Faktory and RabbitMQ, it is essential to be aware of their key differences to make an informed decision on which messaging system best suits your needs.

1. Protocol Support: Faktory primarily uses its proprietary network protocol based on MessagePack, while RabbitMQ supports standard protocols such as AMQP, MQTT, and STOMP.

2. Ease of Use: Faktory is designed to be simple to set up and configure, with a focus on developer-friendly features like a modern REST API. In contrast, RabbitMQ has more configuration options and can be more complex to manage for certain use cases.

3. Message Reliability: RabbitMQ offers more advanced features for message reliability, like publisher confirms, acknowledgments, and persistent messages. On the other hand, Faktory may be more suitable for scenarios where message durability is not a top priority.

4. Scalability: RabbitMQ is known for its robust clustering support, making it easier to scale horizontally and handle higher message volumes. Faktory, while still capable of scaling, might not offer the same level of scalability out of the box.

5. Community and Ecosystem: RabbitMQ boasts a larger and more established user community, along with extensive documentation and plugins. Faktory, being relatively newer, might have a smaller support network and a more limited ecosystem of integrations and tools.

6. Use Cases: RabbitMQ is often preferred for enterprise-grade applications with high message throughput and complex routing requirements. Faktory, on the other hand, might be better suited for smaller projects or environments with a focus on simplicity and ease of use.

Faktory vs RabbitMQ

Overview

Faktory vs RabbitMQ: What are the differences?

Introduction

1. Protocol Support: Faktory primarily uses its proprietary network protocol based on MessagePack, while RabbitMQ supports standard protocols such as AMQP, MQTT, and STOMP.

2. Ease of Use: Faktory is designed to be simple to set up and configure, with a focus on developer-friendly features like a modern REST API. In contrast, RabbitMQ has more configuration options and can be more complex to manage for certain use cases.

3. Message Reliability: RabbitMQ offers more advanced features for message reliability, like publisher confirms, acknowledgments, and persistent messages. On the other hand, Faktory may be more suitable for scenarios where message durability is not a top priority.

4. Scalability: RabbitMQ is known for its robust clustering support, making it easier to scale horizontally and handle higher message volumes. Faktory, while still capable of scaling, might not offer the same level of scalability out of the box.

5. Community and Ecosystem: RabbitMQ boasts a larger and more established user community, along with extensive documentation and plugins. Faktory, being relatively newer, might have a smaller support network and a more limited ecosystem of integrations and tools.

6. Use Cases: RabbitMQ is often preferred for enterprise-grade applications with high message throughput and complex routing requirements. Faktory, on the other hand, might be better suited for smaller projects or environments with a focus on simplicity and ease of use.

Share your Stack

Advice on RabbitMQ, Faktory

Detailed Comparison

What are some alternatives to RabbitMQ, Faktory?

Kafka

Sidekiq

Celery

Amazon SQS

NSQ

ActiveMQ

Beanstalkd

ZeroMQ

Apache NiFi

Gearman

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Faktory vs RabbitMQ

Overview

Faktory vs RabbitMQ: What are the differences?

Introduction

1. Protocol Support: Faktory primarily uses its proprietary network protocol based on MessagePack, while RabbitMQ supports standard protocols such as AMQP, MQTT, and STOMP.

2. Ease of Use: Faktory is designed to be simple to set up and configure, with a focus on developer-friendly features like a modern REST API. In contrast, RabbitMQ has more configuration options and can be more complex to manage for certain use cases.

3. Message Reliability: RabbitMQ offers more advanced features for message reliability, like publisher confirms, acknowledgments, and persistent messages. On the other hand, Faktory may be more suitable for scenarios where message durability is not a top priority.

4. Scalability: RabbitMQ is known for its robust clustering support, making it easier to scale horizontally and handle higher message volumes. Faktory, while still capable of scaling, might not offer the same level of scalability out of the box.

5. Community and Ecosystem: RabbitMQ boasts a larger and more established user community, along with extensive documentation and plugins. Faktory, being relatively newer, might have a smaller support network and a more limited ecosystem of integrations and tools.

6. Use Cases: RabbitMQ is often preferred for enterprise-grade applications with high message throughput and complex routing requirements. Faktory, on the other hand, might be better suited for smaller projects or environments with a focus on simplicity and ease of use.

Share your Stack

Advice on RabbitMQ, Faktory

Detailed Comparison

What are some alternatives to RabbitMQ, Faktory?

Kafka

Sidekiq

Celery

Amazon SQS

NSQ

ActiveMQ

Beanstalkd

ZeroMQ

Apache NiFi

Gearman

Related Comparisons

Bootstrap vs Materialize

Django vs Laravel vs Node.js

Bootstrap vs Foundation vs Material UI

Node.js vs Spring-Boot

Flyway vs Liquibase