Gunicorn vs Unicorn: What are the differences?
Developers describe Gunicorn as "A Python WSGI HTTP Server for UNIX". Gunicorn is a pre-fork worker model ported from Ruby's Unicorn project. The Gunicorn server is broadly compatible with various web frameworks, simply implemented, light on server resources, and fairly speedy. On the other hand, Unicorn is detailed as "Rack HTTP server for fast clients and Unix". Unicorn is an HTTP server for Rack applications designed to only serve fast clients on low-latency, high-bandwidth connections and take advantage of features in Unix/Unix-like kernels. Slow clients should only be served by placing a reverse proxy capable of fully buffering both the the request and response in between Unicorn and slow clients.
Gunicorn and Unicorn can be primarily classified as "Web Servers" tools.
"Python" is the primary reason why developers consider Gunicorn over the competitors, whereas "Fast" was stated as the key factor in picking Unicorn.
Gunicorn and Unicorn are both open source tools. Gunicorn with 5.91K GitHub stars and 1.12K forks on GitHub appears to be more popular than Unicorn with 1.35K GitHub stars and 248 GitHub forks.
reddit, hike, and OpenLabel are some of the popular companies that use Gunicorn, whereas Unicorn is used by Instacart, Shopify, and New Relic. Gunicorn has a broader approval, being mentioned in 184 company stacks & 50 developers stacks; compared to Unicorn, which is listed in 176 company stacks and 55 developer stacks.
What is Gunicorn?
What is Unicorn?
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What tools integrate with Unicorn?
We switched from Unicorn (process model) to Puma (threaded model) to decrease the memory footprint of our Rails production web server. Memory indeed dropped from 6GB to only 1GB!
We just had to decrease our worker count and increase our thread count instead. Performance (response time and throughput) remained the same, if not slightly better. We had no thread-safety errors, which was good.
Free bonus points are:
- Requests are blazing fast on our dev and staging environments!
- Puma has first-class support for WebSockets, so we know for sure that Rails ActionCable or GraphQL subscriptions will work great.
- Being on Puma makes us even more "default Rails"-compliant since it is the default Rails web server these days.
In 2010 we made the very difficult decision to entirely re-engineer our existing monolithic LAMP application from the ground up in order to address some growing concerns about it's long term viability as a platform.
Full application re-write is almost always never the answer, because of the risks involved. However the situation warranted drastic action as it was clear that the existing product was going to face severe scaling issues. We felt it better address these sooner rather than later and also take the opportunity to improve the international architecture and also to refactor the database in. order that it better matched the changes in core functionality.
PostgreSQL was chosen for its reputation as being solid ACID compliant database backend, it was available as an offering AWS RDS service which reduced the management overhead of us having to configure it ourselves. In order to reduce read load on the primary database we implemented an Elasticsearch layer for fast and scalable search operations. Synchronisation of these indexes was to be achieved through the use of Sidekiq's Redis based background workers on Amazon ElastiCache. Again the AWS solution here looked to be an easy way to keep our involvement in managing this part of the platform at a minimum. Allowing us to focus on our core business.
Rails ls was chosen for its ability to quickly get core functionality up and running, its MVC architecture and also its focus on Test Driven Development using RSpec and Selenium with Travis CI providing continual integration. We also liked Ruby for its terse, clean and elegant syntax. Though YMMV on that one!
Unicorn was chosen for its continual deployment and reputation as a reliable application server, nginx for its reputation as a fast and stable reverse-proxy. We also took advantage of the Amazon CloudFront CDN here to further improve performance by caching static assets globally.
We tried to strike a balance between having control over management and configuration of our core application with the convenience of being able to leverage AWS hosted services for ancillary functions (Amazon SES , Amazon SQS Amazon Route 53 all hosted securely inside Amazon VPC of course!).
Whilst there is some compromise here with potential vendor lock in, the tasks being performed by these ancillary services are no particularly specialised which should mitigate this risk. Furthermore we have already containerised the stack in our development using Docker environment, and looking to how best to bring this into production - potentially using Amazon EC2 Container Service
Gunicorn is WSGI container that we used to run our Tornado code as it supports Asynchronous operations on tornado.
Rolling deploys are awesome! We use Unicorn to keep downtime to a minimum as we iterate quickly for our clients.
Gunicorn runs as the HTTP application server. Serves the django application in WSGI mode.