Need advice about which tool to choose?Ask the StackShare community!
Amazon SQS vs Azure Storage: What are the differences?
Introduction
In this article, we will discuss the key differences between Amazon Simple Queue Service (Amazon SQS) and Azure Storage. Both Amazon SQS and Azure Storage are popular cloud-based messaging services that provide reliable and scalable solutions for managing queues and storing data. However, there are several important differences between the two platforms that developers need to consider when choosing the right messaging service for their applications.
Message Delivery Model: Amazon SQS follows a "polling" model, where consumers retrieve messages by repeatedly polling the SQS queue to check for new messages. Azure Storage, on the other hand, uses a "push" model, where consumers are notified through event-driven mechanisms such as Azure Blob Storage triggers or Azure Queue Storage queues.
Message Retention Period: In Amazon SQS, the maximum retention period for a message is 14 days. After this period, the message will be automatically deleted from the queue. Azure Storage provides a similar retention period of up to 7 days for messages in both Azure Queue Storage and Azure Service Bus.
Message Ordering: Amazon SQS guarantees that messages are delivered in the same order they are sent within a single Message Group. Azure Storage, specifically Azure Queue Storage, does not provide inherent support for ordering messages and developers need to implement their own mechanisms for maintaining message order if required.
Visibility Timeout: When a consumer retrieves a message from an Amazon SQS queue, the message becomes temporarily "invisible" to other consumers while the first consumer processes it. This timeout period can be configured by the developer. Azure Storage provides a similar visibility timeout mechanism called "message invisibility timeout" in Azure Queue Storage.
Functionality: Amazon SQS offers a broader range of messaging capabilities, including both standard and FIFO (first-in-first-out) queues, dead-letter queues, and message retention policies. Azure Storage provides Azure Queue Storage, which is a simple FIFO queue, and Azure Service Bus, which provides more advanced messaging features such as pub/sub messaging, message sessions, and dead-lettering.
Availability Zones: Amazon SQS allows developers to choose the availability zone(s) for their queues to ensure high availability and fault tolerance. Azure Storage provides a similar concept of "storage accounts" that are automatically replicated across multiple availability zones in a region for increased availability.
In summary, the key differences between Amazon SQS and Azure Storage include the message delivery model, message retention period, message ordering, visibility timeout mechanism, functionality (including the availability of advanced features), and the concept of availability zones. These differences should be considered based on application requirements when choosing a messaging service.
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 Azure Storage
- All-in-one storage solution24
- Pay only for data used regardless of disk size15
- Shared drive mapping9
- Cost-effective2
- Cheapest hot and cloud storage2
Sign up to add or upvote prosMake informed product decisions
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 Azure Storage
- Direct support is not provided by Azure storage2
