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Amazon MQ vs Amazon SQS: What are the differences?
Introduction
In this article, we will explore the key differences between Amazon MQ and Amazon SQS in the context of their messaging systems.
MQ Broker vs. Message Queue: Amazon MQ is a fully managed message broker service that supports the Apache ActiveMQ and RabbitMQ messaging protocols. It provides a powerful broker-based messaging system that allows for advanced features like message filtering, prioritization, and redelivery policies. On the other hand, Amazon SQS is a managed message queuing service that decouples the components of a distributed application by allowing them to communicate asynchronously. Unlike Amazon MQ, it does not provide a full-fledged broker system and relies on simple message queues instead.
Protocol Support: Amazon MQ supports both the Apache ActiveMQ and RabbitMQ protocols, which have been widely used in enterprise messaging scenarios. It provides compatibility with existing applications built using these protocols, allowing for a smooth transition to the managed service. In contrast, Amazon SQS uses a proprietary protocol and does not support the ActiveMQ or RabbitMQ protocols directly. However, it does provide SDKs and client libraries for different programming languages to simplify the integration process.
Message Persistence: Amazon MQ allows you to choose the level of message persistence based on your use case requirements. It supports both durable and non-durable messaging, where durable messages are stored on disk to ensure reliability even in the event of a system failure. On the other hand, Amazon SQS ensures message durability by storing messages redundantly across multiple availability zones of the region, eliminating the risk of message loss.
Message Delivery: Amazon MQ supports both message push and message pull models. In the push model, the messaging system actively delivers messages to consumers, while in the pull model, consumers actively poll the broker to retrieve messages. This flexibility allows you to design your applications based on the specific requirements. In contrast, Amazon SQS exclusively uses a message pull model, where consumers actively retrieve messages from the queue. The pull model is more suitable for scenarios where the consumer needs to control the rate of message processing.
Throughput and Scalability: Amazon MQ provides greater throughput and scalability compared to Amazon SQS. It supports a higher number of messages per second and concurrent connections, making it suitable for high-volume, high-throughput applications. On the other hand, Amazon SQS is designed for high elasticity, automatically scaling up or down based on the incoming load. It can handle large bursts of traffic without any manual intervention, making it a good choice for applications with unpredictable workloads.
Deployment Complexity: Amazon MQ requires more configuration and management compared to Amazon SQS. As a fully managed message broker service, Amazon MQ requires you to provision and manage the underlying broker instances, including capacity planning, scaling, and installation of updates. In contrast, Amazon SQS abstracts away the infrastructure management, allowing you to focus solely on the messaging logic.
In summary, Amazon MQ provides a robust message broker system with support for multiple protocols, advanced features, and high throughput. On the other hand, Amazon SQS offers a simpler message queuing system with seamless scalability and reliability, ideal for decoupling components in distributed applications.
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 MQ
- Supports low IQ developers7
- Supports existing protocols (JMS, NMS, AMQP, STOMP, …)3
- Easy to migrate existing messaging service2
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
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Cons of Amazon MQ
- Slow AF4
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
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