Gearman vs Resque

Overview

Resque

Stacks118

Followers126

Votes9

GitHub Stars9.5K

Forks1.7K

Gearman

Stacks77

Followers144

Votes45

Gearman vs Resque: What are the differences?

Scalability: Gearman is designed to scale horizontally by adding more worker nodes as needed, while Resque is designed to run on a single server with vertical scaling capabilities for increased performance on that server.
Language Support: Gearman supports multiple programming languages such as C, C++, PHP, Perl, Python, and Ruby for client libraries and workers, whereas Resque is predominantly used with Ruby applications.
Job Queues: Gearman utilizes a centralized job server where clients submit jobs and workers process them, while Resque operates with Redis as a dedicated job queue allowing for efficient job processing and management.
Dependencies: Gearman has minimal dependencies and is lightweight, making it easier to integrate into existing systems, while Resque requires the use of Redis for job queuing, increasing the complexity of the infrastructure.
Monitoring and Reporting: Gearman provides basic monitoring tools like gearadmin for job status and worker information, while Resque lacks built-in monitoring and reporting capabilities, requiring additional tools for performance tracking.
Community and Ecosystem: Gearman has a broader community support with more active contributors and a wider range of plugins and integrations available for various use cases, compared to Resque which has a smaller but dedicated community focused on Ruby development.

In Summary, Gearman and Resque differ in scalability, language support, job queue management, dependencies, monitoring capabilities, and community ecosystem.

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

Resque	Gearman
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.	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.
-	Open Source It’s free! (in both meanings of the word) Gearman has an active open source community that is easy to get involved with if you need help or want to contribute. Worried about licensing? Gearman is BSD;Multi-language - There are interfaces for a number of languages, and this list is growing. You also have the option to write heterogeneous applications with clients submitting work in one language and workers performing that work in another;Flexible - You are not tied to any specific design pattern. You can quickly put together distributed applications using any model you choose, one of those options being Map/Reduce;Fast - Gearman has a simple protocol and interface with an optimized, and threaded, server written in C/C++ to minimize your application overhead;Embeddable - Since Gearman is fast and lightweight, it is great for applications of all sizes. It is also easy to introduce into existing applications with minimal overhead;No single point of failure - Gearman can not only help scale systems, but can do it in a fault tolerant way;No limits on message size - Gearman supports single messages up to 4gig in size. Need to do something bigger? No problem Gearman can chunk messages;Worried about scaling? - Don’t worry about it with Gearman. Craig’s List, Tumblr, Yelp, Etsy,… discover what others have known for years.
Statistics
GitHub Stars 9.5K	GitHub Stars -
GitHub Forks 1.7K	GitHub Forks -
Stacks 118	Stacks 77
Followers 126	Followers 144
Votes 9	Votes 45
Pros & Cons
Pros 5 Free 3 Scalable 1 Easy to use on heroku	Pros 11 Free 11 Ease of use and very simple APIs 6 Polyglot 5 No single point of failure 3 High-throughput

What are some alternatives to Resque, Gearman?

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.

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.

Related Comparisons

Gearman vs Resque: What are the differences?

Scalability: Gearman is designed to scale horizontally by adding more worker nodes as needed, while Resque is designed to run on a single server with vertical scaling capabilities for increased performance on that server.
Language Support: Gearman supports multiple programming languages such as C, C++, PHP, Perl, Python, and Ruby for client libraries and workers, whereas Resque is predominantly used with Ruby applications.
Job Queues: Gearman utilizes a centralized job server where clients submit jobs and workers process them, while Resque operates with Redis as a dedicated job queue allowing for efficient job processing and management.
Dependencies: Gearman has minimal dependencies and is lightweight, making it easier to integrate into existing systems, while Resque requires the use of Redis for job queuing, increasing the complexity of the infrastructure.
Monitoring and Reporting: Gearman provides basic monitoring tools like gearadmin for job status and worker information, while Resque lacks built-in monitoring and reporting capabilities, requiring additional tools for performance tracking.
Community and Ecosystem: Gearman has a broader community support with more active contributors and a wider range of plugins and integrations available for various use cases, compared to Resque which has a smaller but dedicated community focused on Ruby development.

In Summary, Gearman and Resque differ in scalability, language support, job queue management, dependencies, monitoring capabilities, and community ecosystem.

Gearman vs Resque

Overview