Celery vs Kue

Overview

Celery

Stacks1.7K

Followers1.6K

Votes280

GitHub Stars27.5K

Forks4.9K

Kue

Stacks51

Followers88

Votes2

GitHub Stars9.5K

Forks871

Celery vs Kue: What are the differences?

Developers describe Celery as "Distributed task queue". 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. On the other hand, Kue is detailed as "Kue is a priority job queue backed by redis, built for node.js". Kue is a feature rich priority job queue for node.js backed by redis. A key feature of Kue is its clean user-interface for viewing and managing queued, active, failed, and completed jobs.

Celery can be classified as a tool in the "Message Queue" category, while Kue is grouped under "Background Processing".

Celery and Kue are both open source tools. It seems that Celery with 12.7K GitHub stars and 3.3K forks on GitHub has more adoption than Kue with 8.74K GitHub stars and 880 GitHub forks.

Sentry, Ansible, and OpenLabel are some of the popular companies that use Celery, whereas Kue is used by Gigster, Fraeber Labs Pvt Ltd, and Greenkeeper. Celery has a broader approval, being mentioned in 271 company stacks & 77 developers stacks; compared to Kue, which is listed in 6 company stacks and 4 developer stacks.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Detailed Comparison

Celery	Kue
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.	Kue is a feature rich priority job queue for node.js backed by redis. A key feature of Kue is its clean user-interface for viewing and managing queued, active, failed, and completed jobs.
Statistics
GitHub Stars 27.5K	GitHub Stars 9.5K
GitHub Forks 4.9K	GitHub Forks 871
Stacks 1.7K	Stacks 51
Followers 1.6K	Followers 88
Votes 280	Votes 2
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 2 Simple

What are some alternatives to Celery, Kue?

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.