Workflow Automation

mrq

Distributed worker task queue in Python using Redis & gevent.

Status
UnmaintainedNo commits in 2081 days.
Last checked
Checked · Oct 16, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

mrq is a distributed task queue system built with Python, leveraging Redis for message passing and gevent for concurrency. It's designed to handle background tasks efficiently across multiple workers.

mrq stands out by offering a Python-centric approach to distributed task queuing with built-in support for concurrency through gevent, making it ideal for developers who prefer simplicity and efficiency in their background job processing.

When it fits — and when it doesn’t

A good fit for

  • Developers building Python-based systems that require efficient handling of asynchronous tasks.

  • Teams needing a scalable solution for distributed task processing.

Look elsewhere if

  • Projects requiring real-time data streaming and processing, as mrq is designed for batch jobs.

  • Applications where the overhead of Redis and gevent might be prohibitive.

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Performance bottlenecks when Redis becomes a bottleneck

    Redis scalability issues can lead to slower task processing times in high-load scenarios

What it does well

  • Distributed task queue using Redis and gevent for concurrency.

  • Supports Python-based background tasks.

  • Flexible configuration options for scaling.

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

How Fast Is It?

Set up mrq

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →