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  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Background Processing
  5. Faktory vs Hangfire

Faktory vs Hangfire

OverviewComparisonAlternatives

Overview

Hangfire
Hangfire
Stacks333
Followers249
Votes17
GitHub Stars9.9K
Forks1.7K
Faktory
Faktory
Stacks7
Followers27
Votes3
GitHub Stars6.0K
Forks236

Faktory vs Hangfire: What are the differences?

  1. Scalability: Faktory allows horizontal scaling, meaning multiple workers can be distributed across different machines, enabling efficient utilization of resources. Hangfire, on the other hand, supports vertical scaling by utilizing the available resources on a single machine. This difference in scalability approach allows Faktory to handle larger workloads and accommodate more concurrent requests compared to Hangfire.

  2. Job Dependency Management: Faktory provides a built-in mechanism for handling job dependencies, allowing jobs to be executed only after specific prerequisites are met. Hangfire, on the contrary, lacks this feature and does not offer native support for job dependency management. This distinction makes Faktory a preferable choice when complex dependencies between jobs need to be managed.

  3. Persistence: Faktory offers persistent job storage, ensuring that even if the system restarts or crashes, the job data is not lost. Hangfire, on the other hand, relies on in-memory storage options, making it susceptible to data loss in case of system failures. This difference in persistence capabilities makes Faktory more reliable and suitable for critical applications where data integrity is crucial.

  4. Delayed Jobs: Faktory allows for scheduling jobs to be executed at a specific future time or after a certain delay. Hangfire, on the other hand, lacks native support for such delayed job execution and requires additional customization with external libraries or implementations. This distinction makes Faktory a more convenient choice when precise job scheduling and time-sensitive operations are required.

  5. Web Interface: Hangfire provides a user-friendly web interface that allows easy monitoring and management of jobs, providing detailed information and statistics. Faktory, on the other hand, does not offer a native web interface, requiring integration with third-party tools or custom development for job monitoring and management. This difference in out-of-the-box functionality makes Hangfire a more convenient choice for developers who prefer a ready-to-use monitoring interface.

  6. Language Support: Faktory offers official client libraries for various programming languages, including Python, Ruby, and Go, making it compatible with a wide range of development stacks. Hangfire, on the other hand, primarily focuses on .NET technologies and lacks official support for other programming languages. This distinction in language support makes Faktory a more versatile choice for developers working with different programming languages.

In Summary, Faktory stands out from Hangfire with its scalability, built-in job dependency management, persistent job storage, native support for delayed jobs, language support beyond .NET, while Hangfire excels in providing a user-friendly web interface for job monitoring and management.

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Detailed Comparison

Hangfire
Hangfire
Faktory
Faktory

It is an open-source framework that helps you to create, process and manage your background jobs, i.e. operations you don't want to put in your request processing pipeline. It supports all kind of background tasks – short-running and long-running, CPU intensive and I/O intensive, one shot and recurrent.

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.

Statistics
GitHub Stars
9.9K
GitHub Stars
6.0K
GitHub Forks
1.7K
GitHub Forks
236
Stacks
333
Stacks
7
Followers
249
Followers
27
Votes
17
Votes
3
Pros & Cons
Pros
  • 7
    Integrated UI dashboard
  • 5
    Simple
  • 3
    Robust
  • 2
    In Memory
  • 0
    Simole
Pros
  • 2
    Worker language agnostic
  • 1
    Simple service API
Integrations
No integrations available
Node.js
Node.js
Ruby
Ruby
Python
Python
Golang
Golang
Elixir
Elixir
PHP
PHP
Java
Java
JavaScript
JavaScript

What are some alternatives to Hangfire, Faktory?

Sidekiq

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.

Beanstalkd

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.

Resque

Resque

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.

delayed_job

delayed_job

Delayed_job (or DJ) encapsulates the common pattern of asynchronously executing longer tasks in the background. It is a direct extraction from Shopify where the job table is responsible for a multitude of core tasks.

Kue

Kue

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.

Bull

Bull

The fastest, most reliable, Redis-based queue for Node. Carefully written for rock solid stability and atomicity.

Cron

Cron

Background-only application which launches and runs other applications, or opens documents, at specified dates and times.

PHP-FPM

PHP-FPM

It is an alternative PHP FastCGI implementation with some additional features useful for sites of any size, especially busier sites. It includes Adaptive process spawning, Advanced process management with graceful stop/start, Emergency restart in case of accidental opcode cache destruction etc.

Que

Que

Que is a high-performance alternative to DelayedJob or QueueClassic that improves the reliability of your application by protecting your jobs with the same ACID guarantees as the rest of your data.

Goose

Goose

It is a simple, reliable & scalable background processing library for Clojure. It has a transparent design & cloud-native architecture.

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