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Celery vs Sparrow: What are the differences?
Introduction: Here are the key differences between Celery and Sparrow.
Scalability: Celery is highly scalable and can handle a large number of tasks concurrently, making it suitable for complex applications with heavy workloads. On the other hand, Sparrow is more lightweight and may not be as reliable for handling a large volume of tasks simultaneously.
Ease of Use: Celery offers a more comprehensive set of features and functionalities, making it a preferred choice for developers who require advanced task management capabilities. In contrast, Sparrow is simpler and more straightforward, making it easier for beginners to set up and use without the complexity of Celery.
Community Support: Celery has a larger and more active community of developers and users, providing a wealth of resources, documentation, and support for troubleshooting and learning. Sparrow, being a newer and less widely adopted framework, may have a smaller community and fewer resources available for help and guidance.
Integration: Celery integrates seamlessly with various frameworks, message brokers, and backend storage systems, offering more flexibility and compatibility with different tools and technologies in the development stack. Sparrow, being a lightweight framework, may have limited integration options and may not provide the same level of flexibility as Celery.
Performance: Celery is known for its high performance and efficiency in task execution, thanks to its robust architecture and optimization for handling concurrent operations. Sparrow, while efficient for smaller tasks and simple workflows, may not offer the same level of performance and speed as Celery for more demanding applications.
Maintenance: Celery has been around for a longer time and has undergone multiple updates and improvements, ensuring better stability, security, and long-term maintenance for projects using the framework. Sparrow, being relatively new, may lack the same level of maturity and ongoing support for addressing bugs, security vulnerabilities, and evolving needs over time.
In Summary, when choosing between Celery and Sparrow, consider factors such as scalability, ease of use, community support, integration capabilities, performance, and maintenance requirements to determine the best fit for your project.
I am just a beginner at these two technologies.
Problem statement: I am getting lakh of users from the sequel server for whom I need to create caches in MongoDB by making different REST API requests.
Here these users can be treated as messages. Each REST API request is a task.
I am confused about whether I should go for RabbitMQ alone or Celery.
If I have to go with RabbitMQ, I prefer to use python with Pika module. But the challenge with Pika is, it is not thread-safe. So I am not finding a way to execute a lakh of API requests in parallel using multiple threads using Pika.
If I have to go with Celery, I don't know how I can achieve better scalability in executing these API requests in parallel.
For large amounts of small tasks and caches I have had good luck with Redis and RQ. I have not personally used celery but I am fairly sure it would scale well, and I have not used RabbitMQ for anything besides communication between services. If you prefer python my suggestions should feel comfortable.
Sorry I do not have a more information
Pros of Celery
- Task queue99
- Python integration63
- Django integration40
- Scheduled Task30
- Publish/subsribe19
- Various backend broker8
- Easy to use6
- Great community5
- Workflow5
- Free4
- Dynamic1
Pros of Sparrow
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Cons of Celery
- Sometimes loses tasks4
- Depends on broker1