Celery vs Resque | What are the differences? | StackShare

Celery vs Resque

Overview

Celery

Stacks1.6K

Followers1.6K

Votes280

GitHub Stars27.5K

Forks4.9K

Resque

Stacks119

Followers126

Votes9

GitHub Stars9.5K

Forks1.7K

Celery vs Resque: What are the differences?

1. **Language**: Celery is written in Python, while Resque is written in Ruby. 2. **Serialization**: Celery uses JSON and MessagePack for serialization, whereas Resque uses only JSON. 3. **Dependencies**: Celery has more dependencies compared to Resque, making setup a bit more complex. 4. **Database support**: Celery supports various backends like RabbitMQ, Redis, and Amazon SQS, whereas Resque primarily uses Redis. 5. **Monitoring**: Celery provides real-time monitoring with tools like Flower, while Resque does not have built-in monitoring tools. 6. **Community**: Celery has a larger community and more extensive documentation compared to Resque.

In Summary, Celery and Resque differ in language, serialization, dependencies, database support, monitoring, and community size.

Advice on Celery, Resque

Shantha

Sep 30, 2020

Needs adviceon

RabbitMQ

Celery

MongoDB

I am just a beginner at these two technologies.

Problem statement: I am getting lakh of users from the sequel server for whom I need to create caches in MongoDB by making different REST API requests.

Here these users can be treated as messages. Each REST API request is a task.

I am confused about whether I should go for RabbitMQ alone or Celery.

If I have to go with RabbitMQ, I prefer to use python with Pika module. But the challenge with Pika is, it is not thread-safe. So I am not finding a way to execute a lakh of API requests in parallel using multiple threads using Pika.

If I have to go with Celery, I don't know how I can achieve better scalability in executing these API requests in parallel.

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Comments

Detailed Comparison

Celery	Resque
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.	Background jobs can be any Ruby class or module that responds to perform. Your existing classes can easily be converted to background jobs or you can create new classes specifically to do work. Or, you can do both.
Statistics
GitHub Stars 27.5K	GitHub Stars 9.5K
GitHub Forks 4.9K	GitHub Forks 1.7K
Stacks 1.6K	Stacks 119
Followers 1.6K	Followers 126
Votes 280	Votes 9
Pros & Cons
Pros 99 Task queue 63 Python integration 40 Django integration 30 Scheduled Task 19 Publish/subsribe Cons 4 Sometimes loses tasks 1 Depends on broker	Pros 5 Free 3 Scalable 1 Easy to use on heroku

What are some alternatives to Celery, Resque?

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.

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.

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.