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Azure Storage vs Celery: What are the differences?
Azure Storage and Celery are two different technologies used in the development of web applications. While Azure Storage is a service provided by Microsoft Azure for storing different types of data, Celery is a distributed task queue system.
Scalability: Azure Storage is highly scalable and can handle large amounts of data without compromising performance. It provides features like automatic scaling, geo-replication, and load balancing. On the other hand, Celery is designed for distributing tasks across multiple workers, allowing applications to scale horizontally by adding more workers as needed.
Data Types: Azure Storage supports various data types such as blobs, tables, queues, and files, providing different ways to store and retrieve data. It offers built-in features for managing large amounts of structured and unstructured data. In contrast, Celery focuses primarily on managing and distributing tasks among workers, with less emphasis on specific data types.
Integration: Azure Storage is tightly integrated with other services provided by Microsoft Azure, such as Azure Functions, Azure Logic Apps, and Azure Databricks. It can be easily used as a storage solution for these services. On the other hand, Celery can be integrated with various frameworks and technologies, providing flexibility in the choice of tools and libraries.
Message Brokering: Celery utilizes a message broker to handle task distribution among workers. It supports multiple message brokers like RabbitMQ, Redis, and Amazon SQS. This allows applications to use different message brokers based on their specific requirements. Azure Storage, on the other hand, does not provide built-in message brokering capabilities, as it is primarily focused on data storage.
Monitoring and Management: Azure Storage provides comprehensive monitoring and management tools, allowing users to track the performance, usage, and availability of their storage accounts. It offers features like Azure Monitor, Azure Resource Manager, and Azure Storage Explorer. In contrast, Celery does not have built-in monitoring and management tools, but it can be integrated with third-party tools for this purpose.
Pricing Model: Azure Storage follows a pay-as-you-go pricing model, where users are charged based on the amount of storage used and the operations performed on the data. The pricing is flexible and allows users to choose different levels of performance and durability. Celery, being an open-source technology, does not have a specific pricing model. However, users might incur costs related to the infrastructure required to run Celery workers and message brokers.
In Summary, Azure Storage is a scalable and versatile data storage solution tightly integrated with other Azure services, while Celery is a distributed task queue system that focuses on task distribution among workers.
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 Azure Storage
- All-in-one storage solution24
- Pay only for data used regardless of disk size15
- Shared drive mapping9
- Cost-effective2
- Cheapest hot and cloud storage2
Pros of Celery
- Task queue99
- Python integration63
- Django integration40
- Scheduled Task30
- Publish/subsribe19
- Various backend broker8
- Easy to use6
- Great community5
- Workflow5
- Free4
- Dynamic1
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Cons of Azure Storage
- Direct support is not provided by Azure storage2
Cons of Celery
- Sometimes loses tasks4
- Depends on broker1