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Amazon SQS vs Beanstalkd: What are the differences?
Introduction:
Amazon Simple Queue Service (SQS) and Beanstalkd are both messaging systems that are commonly used for building distributed applications. While they have some similarities in terms of their purpose, there are several key differences between the two.
Message Persistence and Durability: Amazon SQS provides the option to make messages persistent and durable by storing them redundantly across multiple availability zones, ensuring message reliability even in the event of failures. On the other hand, Beanstalkd does not have built-in persistent storage capabilities, so messages are stored in memory only, which means they can be lost in the event of an unexpected failure.
Scalability and Message Volume: Amazon SQS is highly scalable and can handle a vast number of messages, making it suitable for applications that deal with high message volumes. It automatically scales horizontally to accommodate incoming messages. Beanstalkd, on the other hand, has limited scalability as it is designed to run on a single server, making it more suitable for smaller applications with lower message volumes.
Message Delivery Order: Amazon SQS guarantees the order of message delivery within a single queue, ensuring the first message sent is the first to be received. It provides a strictly ordered message processing system. Beanstalkd, on the other hand, does not guarantee the order of message delivery, making it more suitable for scenarios where message order is not essential.
Visibility Timeout: Amazon SQS provides a visibility timeout feature that allows a consumer to reserve a message for a specified period of time, preventing other consumers from processing it. Beanstalkd, on the other hand, does not have a built-in visibility timeout mechanism.
Integration and Ecosystem: Amazon SQS is part of the broader Amazon Web Services (AWS) ecosystem, which provides a wide range of services and integrations. It can easily be integrated with other AWS services like Amazon S3, Lambda, and more. Beanstalkd, on the other hand, is a standalone open-source messaging system and does not have the level of integration and ecosystem that AWS provides.
Deployment and Management: Amazon SQS is a fully managed service, which means AWS takes care of operational aspects such as deployment, monitoring, and maintenance. On the other hand, Beanstalkd requires manual setup and management, making it more suitable for applications where developers have more control over the infrastructure.
In summary, Amazon SQS and Beanstalkd differ in terms of message persistence, scalability, message delivery order, visibility timeout, integration, and management. Amazon SQS offers message durability and scalability with strict ordering, while Beanstalkd provides a lightweight solution without persistence and limited scalability.
Hi! I am creating a scraping system in Django, which involves long running tasks between 1 minute & 1 Day. As I am new to Message Brokers and Task Queues, I need advice on which architecture to use for my system. ( Amazon SQS, RabbitMQ, or Celery). The system should be autoscalable using Kubernetes(K8) based on the number of pending tasks in the queue.
Hello, i highly recommend Apache Kafka, to me it's the best. You can deploy it in cluster mode inside K8S, thus you can have a Highly available system (also auto scalable).
Good luck
Hi, we are in a ZMQ set up in a push/pull pattern, and we currently start to have more traffic and cases that the service is unavailable or stuck. We want to: * Not loose messages in services outages * Safely restart service without losing messages (ZeroMQ seems to need to close the socket in the receiver before restart manually)
Do you have experience with this setup with ZeroMQ? Would you suggest RabbitMQ or Amazon SQS (we are in AWS setup) instead? Something else?
Thank you for your time
ZeroMQ is fast but you need to build build reliability yourself. There are a number of patterns described in the zeromq guide. I have used RabbitMQ before which gives lot of functionality out of the box, you can probably use the worker queues example from the tutorial, it can also persists messages in the queue.
I haven't used Amazon SQS before. Another tool you could use is Kafka.
Both would do the trick, but there are some nuances. We work with both.
From the sound of it, your main focus is "not losing messages". In that case, I would go with RabbitMQ with a high availability policy (ha-mode=all) and a main/retry/error queue pattern.
Push messages to an exchange, which sends them to the main queue. If an error occurs, push the errored out message to the retry exchange, which forwards it to the retry queue. Give the retry queue a x-message-ttl and set the main exchange as a dead-letter-exchange. If your message has been retried several times, push it to the error exchange, where the message can remain until someone has time to look at it.
This is a very useful and resilient pattern that allows you to never lose messages. With the high availability policy, you make sure that if one of your rabbitmq nodes dies, another can take over and messages are already mirrored to it.
This is not really possible with SQS, because SQS is a lot more focused on throughput and scaling. Combined with SNS it can do interesting things like deduplication of messages and such. That said, one thing core to its design is that messages have a maximum retention time. The idea is that a message that has stayed in an SQS queue for a while serves no more purpose after a while, so it gets removed - so as to not block up any listener resources for a long time. You can also set up a DLQ here, but these similarly do not hold onto messages forever. Since you seem to depend on messages surviving at all cost, I would suggest that the scaling/throughput benefit of SQS does not outweigh the difference in approach to messages there.
I want to schedule a message. Amazon SQS provides a delay of 15 minutes, but I want it in some hours.
Example: Let's say a Message1 is consumed by a consumer A but somehow it failed inside the consumer. I would want to put it in a queue and retry after 4hrs. Can I do this in Amazon MQ? I have seen in some Amazon MQ videos saying scheduling messages can be done. But, I'm not sure how.
Mithiridi, I believe you are talking about two different things. 1. If you need to process messages with delays of more 15m or at specific times, it's not a good idea to use queues, independently of tool SQM, Rabbit or Amazon MQ. you should considerer another approach using a scheduled job. 2. For dead queues and policy retries RabbitMQ, for example, doesn't support your use case. https://medium.com/@kiennguyen88/rabbitmq-delay-retry-schedule-with-dead-letter-exchange-31fb25a440fc I'm not sure if that is possible SNS/SQS support, they have a maximum delay for delivery (maxDelayTarget) in seconds but it's not clear the number. You can check this out: https://docs.aws.amazon.com/sns/latest/dg/sns-message-delivery-retries.html
Pros of Amazon SQS
- Easy to use, reliable62
- Low cost40
- Simple28
- Doesn't need to maintain it14
- It is Serverless8
- Has a max message size (currently 256K)4
- Triggers Lambda3
- Easy to configure with Terraform3
- Delayed delivery upto 15 mins only3
- Delayed delivery upto 12 hours3
- JMS compliant1
- Support for retry and dead letter queue1
- D1
Pros of Beanstalkd
- Fast23
- Free12
- Does one thing well12
- Scalability9
- Simplicity8
- External admin UI developer friendly3
- Job delay3
- Job prioritization2
- External admin UI2
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Cons of Amazon SQS
- Has a max message size (currently 256K)2
- Proprietary2
- Difficult to configure2
- Has a maximum 15 minutes of delayed messages only1
Cons of Beanstalkd
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