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Amazon SQS vs Resque: What are the differences?
Key differences between Amazon SQS and Resque
Message transport: One of the main differences between Amazon Simple Queue Service (SQS) and Resque is the way they handle message transport. SQS is a fully managed message queuing service that uses a distributed system to reliably deliver messages between distributed components. On the other hand, Resque is a Redis-backed Ruby library for creating background jobs and processing them with multiple workers.
Message persistence: Another key difference is the way messages are persisted. In SQS, messages are stored redundantly across multiple availability zones to ensure durability. This means that even if one availability zone goes down, the messages are still available for consumption. Resque, on the other hand, stores messages in Redis, which may not have the same level of redundancy by default. However, Redis does offer various replication options that can be used to achieve a similar level of durability.
Message ordering: SQS guarantees that messages will be delivered in the order they were sent, making it suitable for scenarios that require strict message ordering. In contrast, Resque does not inherently provide message ordering guarantees. Messages processed by Resque can be executed in parallel by multiple workers, which may cause the order of execution to be different from the order in which they were received.
Job processing: SQS focuses on asynchronous, distributed message processing, allowing for high scalability and fault tolerance. It provides features like message visibility timeouts and delayed message delivery. Resque, on the other hand, is specifically designed for processing background jobs in Ruby. It allows developers to enqueue and process jobs asynchronously, but it may not have the same level of scalability and fault tolerance as SQS.
Service management: Amazon SQS is a fully managed service provided by Amazon Web Services (AWS). This means that AWS takes care of the underlying infrastructure, including scaling, availability, and maintenance. Resque, on the other hand, requires manual management and administration of the infrastructure it runs on. This includes setting up and configuring Redis, managing worker processes, and ensuring high availability.
Integration with AWS ecosystem: As an AWS service, SQS seamlessly integrates with other AWS services like AWS Lambda, Amazon S3, and Amazon EC2. It provides easy-to-use SDKs for various programming languages and offers features that support event-driven architectures. Resque, being a Ruby library, may require additional effort to integrate with other AWS services and may not have the same level of native support and compatibility.
In summary, Amazon SQS and Resque differ in their approach to message transport, message persistence, message ordering, job processing, service management, and integration with the AWS ecosystem. SQS is a fully managed message queuing service focused on highly scalable and fault-tolerant distributed processing, while Resque is a Ruby library for background job processing that requires manual management and may not have the same level of scalability and native support.
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 Resque
- Free5
- Scalable3
- Easy to use on heroku1
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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