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Celery

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265
Sandglass

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Celery vs Sandglass: What are the differences?

Celery: 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; Sandglass: Distributed, scalable, persistent time-sorted message queue. A distributed, horizontally scalable, persistent, time ordered message queue. Developed to support asynchronous tasks and message scheduling which makes it suitable for usage as a task queue.

Celery and Sandglass can be categorized as "Message Queue" tools.

Celery and Sandglass are both open source tools. It seems that Celery with 12.9K GitHub stars and 3.33K forks on GitHub has more adoption than Sandglass with 1.52K GitHub stars and 40 GitHub forks.

Advice on Celery and Sandglass
Needs advice
on
RabbitMQ
and
Celery

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.

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Replies (1)
Recommends
Redis
rq

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

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Pros of Celery
Pros of Sandglass
  • 94
    Task queue
  • 61
    Python integration
  • 37
    Django integration
  • 29
    Scheduled Task
  • 18
    Publish/subsribe
  • 6
    Easy to use
  • 6
    Various backend broker
  • 5
    Great community
  • 4
    Workflow
  • 4
    Free
  • 1
    Dynamic
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    Cons of Celery
    Cons of Sandglass
    • 4
      Sometimes loses tasks
    • 1
      Depends on broker
      Be the first to leave a con

      Sign up to add or upvote consMake informed product decisions

      What is Celery?

      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.

      What is Sandglass?

      A distributed, horizontally scalable, persistent, time ordered message queue. Developed to support asynchronous tasks and message scheduling which makes it suitable for usage as a task queue.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Celery?
      What companies use Sandglass?
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        What tools integrate with Celery?
        What tools integrate with Sandglass?

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        What are some alternatives to Celery and Sandglass?
        RabbitMQ
        RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
        Kafka
        Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
        Airflow
        Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
        Cucumber
        Cucumber is a tool that supports Behaviour-Driven Development (BDD) - a software development process that aims to enhance software quality and reduce maintenance costs.
        Amazon SQS
        Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.
        See all alternatives