Celery vs IronMQ: What are the differences?
Developers describe Celery as "Distributed task queue". 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. On the other hand, IronMQ is detailed as "Message Queue for any deployment". An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.
Celery and IronMQ can be primarily classified as "Message Queue" tools.
"Task queue" is the top reason why over 84 developers like Celery, while over 10 developers mention "Great Support" as the leading cause for choosing IronMQ.
Celery is an open source tool with 12.9K GitHub stars and 3.33K GitHub forks. Here's a link to Celery's open source repository on GitHub.
Udemy, Robinhood, and Sentry are some of the popular companies that use Celery, whereas IronMQ is used by HotelTonight, Coinbase, and Hubble. Celery has a broader approval, being mentioned in 272 company stacks & 77 developers stacks; compared to IronMQ, which is listed in 9 company stacks and 5 developer stacks.
What is Celery?
What is IronMQ?
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I deploy to Heroku. However, my applications require full linux applications that cannot be deployed to Heroku. I deploy them to Rackspace.
Then Heroku and Rackspace communicate over IronMQ. Problem solved.
All of our background jobs (e.g., image resizing, file uploading, email and SMS sending) are done through Celery (using Redis as its broker). Celery's scheduling and retrying features are especially useful for error-prone tasks, such as email and SMS sending.
For orchestrating the creation of the correct number of instances, managing errors and retries, and finally managing the deallocation of resources we use RabbitMQ in conjunction with the Celery Project framework, along with a self-developed workflow engine.
We maintain a fork of Celery 3 that adds HTTPS support for Redis brokers. The Winning Model currently uses Celery 3 because Celery 4 dropped support for Windows.
We plan on migrating to Celery 4 once Azure ASE supports Linux apps
We used celery, in combination with RabbitMQ and celery-beat, to run periodic tasks, as well as some user-initiated long-running tasks on the server.
Using Celery, the web service creates tasks that are executed by a background worker. Celery uses a RabbitMQ instance as a task queue.