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ActiveMQ vs Amazon SQS: What are the differences?
ActiveMQ is an open-source message broker that supports multiple messaging protocols, while Amazon SQS (Simple Queue Service) is a fully managed message queuing service provided by AWS. Let's explore the key differences between them.
Message Delivery Model: ActiveMQ follows a traditional message queue model, where the messages are stored in queues and clients consume them in a sequential order. On the other hand, Amazon SQS follows a distributed messaging model, where messages are automatically distributed among multiple queues and processing is parallelized. This provides better scalability and fault tolerance.
Message Ordering: ActiveMQ guarantees the ordered delivery of messages within a single queue, ensuring that messages are consumed in the same order as they are produced. In contrast, Amazon SQS does not guarantee strict ordering of messages, as it distributes messages across different servers and processing can happen in parallel. However, you can use message groups in Amazon SQS to ensure ordering of messages within a specific group.
Message Persistence: ActiveMQ stores messages in a persistent manner, ensuring that they are not lost even in the case of server failures. It provides options for different persistence stores, such as relational databases or file systems. On the other hand, Amazon SQS stores messages redundantly across multiple availability zones, providing durability and high availability. It does not provide direct control over the persistence of individual messages.
Message Visibility: ActiveMQ allows consumers to acknowledge the receipt of messages, making them invisible to other consumers. This ensures exclusive processing of messages by a single consumer. In Amazon SQS, messages become invisible as soon as they are received by a consumer. However, if the consumer fails to process the message within a specified visibility timeout period, the message becomes visible again and can be consumed by another consumer.
Message Size Limit: ActiveMQ has a limit on the maximum size of messages that can be processed. The limit is typically based on the underlying persistence store. Amazon SQS supports larger message sizes compared to ActiveMQ. The maximum message size in Amazon SQS is 256KB for standard queues and 2GB for FIFO queues.
Message Delay: ActiveMQ does not provide a built-in delay mechanism for delivering messages. However, it can be achieved using custom code or frameworks built on top of ActiveMQ. In Amazon SQS, you can set a delay on individual messages, specifying the time to wait before making the message visible to consumers. This can be useful in scenarios where messages need to be processed after a specific delay.
In summary, ActiveMQ follows a traditional message queue model with strict ordering and more control over persistence and message visibility. Amazon SQS, on the other hand, follows a distributed messaging model with automatic distribution and parallel processing, providing scalability and high availability. It has features such as message groups, larger message size support, and a built-in delay mechanism.
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 ActiveMQ
- Easy to use18
- Open source14
- Efficient13
- JMS compliant10
- High Availability6
- Scalable5
- Distributed Network of brokers3
- Persistence3
- Support XA (distributed transactions)3
- Docker delievery1
- Highly configurable1
- RabbitMQ0
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 ActiveMQ
- ONLY Vertically Scalable1
- Support1
- Low resilience to exceptions and interruptions1
- Difficult to scale1
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