Django Q2 vs Faktory

Django Q2 is a Django task queue, scheduler and worker application built around Python multiprocessing. It runs asynchronous tasks with worker pools and supports scheduled, cron and repeated jobs. For task workflows, it offers result hooks, groups and chains. A multi-cluster monitor and Django Admin integration provide monitoring options. Brokers include Redis, IronMQ, Amazon SQS, MongoDB and Django ORM; the project also lists Rollbar and Sentry support for error reporting. Signed and compressed packages are among its listed security features. The documentation says it is tested with Python 3.10 through 3.14 and works with Django 5.2, 6.0 and 6.1. It is self-hosted, with the README describing compatibility with PaaS deployment across multiple instances. The project is free, MIT-licensed software, installed with pip using the package name django-q2. Listed platforms are Linux, macOS, self-hosted and web. Disque support has been dropped.

Faktory is a persistent background job system that works across programming languages. It includes a responsive web interface for viewing and managing jobs, and uses Redis as a child process for local storage, persisting data to its configured directory. The maker lists worker bindings for Node/JavaScript, Ruby, Go, Python, PHP, Elixir, Rust, Swift, Crystal, Haskell, Java/JVM,.NET, and Clojure. Linux RPM and DEB packages, macOS Homebrew installation, and a Docker image are documented. Faktory supports TLS for worker and HTTP ports, with clients authenticated by a configured global password. The OSS edition is free under AGPL and has no dedicated support. Enterprise features include cron jobs, unique and expiring jobs, Redis Gateway, StatsD metrics, queue throttling, batches or workflows, and job status. Enterprise production use requires a valid license and is limited to purchased connections: the first pack is $299 a month for 100 connections, and each additional pack is $99 a month for 100 connections. Faktory does not provide clustered high availability; persistence and failover rely on Redis replication.