Celery vs ejabberd

Overview

Celery

Stacks1.7K

Followers1.6K

Votes280

GitHub Stars27.5K

Forks4.9K

ejabberd

Stacks33

Followers48

Votes0

GitHub Stars6.5K

Forks1.5K

Celery vs ejabberd: What are the differences?

What is Celery? 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.

What is ejabberd? A scalable and robust instant messaging server. It is a distributed, fault-tolerant technology that allows the creation of large-scale instant messaging applications. The server can reliably support thousands of simultaneous users on a single node and has been designed to provide exceptional standards of fault tolerance.

Celery and ejabberd can be categorized as "Message Queue" tools.

Celery and ejabberd are both open source tools. Celery with 13.1K GitHub stars and 3.36K forks on GitHub appears to be more popular than ejabberd with 4.18K GitHub stars and 1.25K GitHub forks.

According to the StackShare community, Celery has a broader approval, being mentioned in 355 company stacks & 455 developers stacks; compared to ejabberd, which is listed in 5 company stacks and 3 developer stacks.

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CLI (Node.js)

Manual

Detailed Comparison

Celery	ejabberd
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.	It is a distributed, fault-tolerant technology that allows the creation of large-scale instant messaging applications. The server can reliably support thousands of simultaneous users on a single node and has been designed to provide exceptional standards of fault tolerance.
-	Cross-platform; Administrator-friendly; Internationalized; Fault-tolerant
Statistics
GitHub Stars 27.5K	GitHub Stars 6.5K
GitHub Forks 4.9K	GitHub Forks 1.5K
Stacks 1.7K	Stacks 33
Followers 1.6K	Followers 48
Votes 280	Votes 0
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	No community feedback yet
Integrations
No integrations available	PostgreSQL Linux MySQL Mac OS X

What are some alternatives to Celery, ejabberd?

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.

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.

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.

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.

IronMQ

An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.