When would I use SNS versus SQS, and why are they always coupled together?
SNS is a distributed publish-subscribe system. Messages are pushed to subscribers as and when they are sent by publishers to SNS.
SQS is distributed queuing system. Messages are not pushed to receivers. Receivers have to poll or pull messages from SQS. Messages can't be received by multiple receivers at the same time. Any one receiver can receive a message, process and delete it. Other receivers do not receive the same message later. Polling inherently introduces some latency in message delivery in SQS unlike SNS where messages are immediately pushed to subscribers. SNS supports several end points such as email, SMS, HTTP end point and SQS. If you want unknown number and type of subscribers to receive messages, you need SNS.
You don't have to couple SNS and SQS always. You can have SNS send messages to email, SMS or HTTP end point apart from SQS. There are advantages to coupling SNS with SQS. You may not want an external service to make connections to your hosts (a firewall may block all incoming connections to your host from outside).
Your end point may just die because of heavy volume of messages. Email and SMS maybe not your choice of processing messages quickly. By coupling SNS with SQS, you can receive messages at your pace. It allows clients to be offline, tolerant to network and host failures. You also achieve guaranteed delivery. If you configure SNS to send messages to an HTTP end point or email or SMS, several failures to send message may result in messages being dropped.
SQS is mainly used to decouple applications or integrate applications. Messages can be stored in SQS for a short duration of time (maximum 14 days). SNS distributes several copies of messages to several subscribers. For example, let’s say you want to replicate data generated by an application to several storage systems. You could use SNS and send this data to multiple subscribers, each replicating the messages it receives to different storage systems (S3, hard disk on your host, database, etc.).
SQS
a message is Pushed into the queue, which is still a single point of failure. Change my mind. –
Inbound Here's a comparison of the two:
Entity Type
- SQS: Queue (Similar to JMS)
- SNS: Topic (Pub/Sub system)
Message consumption
- SQS: Pull Mechanism - Consumers poll and pull messages from SQS
- SNS: Push Mechanism - SNS Pushes messages to consumers
Use Case
- SQS: Decoupling two applications and allowing parallel asynchronous processing
- SNS: Fanout - Processing the same message in multiple ways
Persistence
- SQS: Messages are persisted for some (configurable) duration if no consumer is available (maximum two weeks), so the consumer does not have to be up when messages are added to queue.
- SNS: No persistence. Whichever consumer is present at the time of message arrival gets the message and the message is deleted. If no consumers are available then the message is lost after a few retries.
Consumer Type
- SQS: All the consumers are typically identical and hence process the messages in the exact same way (each message is processed once by one consumer, though in rare cases messages may be resent)
- SNS: The consumers might process the messages in different ways
Sample applications
- SQS: Jobs framework: The Jobs are submitted to SQS and the consumers at the other end can process the jobs asynchronously. If the job frequency increases, the number of consumers can simply be increased to achieve better throughput.
- SNS: Image processing. If someone uploads an image to S3 then watermark that image, create a thumbnail and also send a Thank You email. In that case S3 can publish notifications to an SNS topic with three consumers listening to it. The first one watermarks the image, the second one creates a thumbnail and the third one sends a Thank You email. All of them receive the same message (image URL) and do their processing in parallel.
You can see SNS as a traditional topic which you can have multiple Subscribers. You can have heterogeneous subscribers for one given SNS topic, including Lambda and SQS, for example. You can also send SMS messages or even e-mails out of the box using SNS. One thing to consider in SNS is only one message (notification) is received at once, so you cannot take advantage from batching.
SQS, on the other hand, is nothing but a queue, where you store messages and subscribe one consumer (yes, you can have N consumers to one SQS queue, but it would get messy very quickly and way harder to manage considering all consumers would need to read the message at least once, so one is better off with SNS combined with SQS for this use case, where SNS would push notifications to N SQS queues and every queue would have one subscriber, only) to process these messages. As of Jun 28, 2018, AWS Supports Lambda Triggers for SQS, meaning you don't have to poll for messages any more.
Furthermore, you can configure a DLQ on your source SQS queue to send messages to in case of failure. In case of success, messages are automatically deleted (this is another great improvement), so you don't have to worry about the already processed messages being read again in case you forgot to delete them manually. I suggest taking a look at Lambda Retry Behaviour to better understand how it works.
One great benefit of using SQS is that it enables batch processing. Each batch can contain up to 10 messages, so if 100 messages arrive at once in your SQS queue, then 10 Lambda functions will spin up (considering the default auto-scaling behaviour for Lambda) and they'll process these 100 messages (keep in mind this is the happy path as in practice, a few more Lambda functions could spin up reading less than the 10 messages in the batch, but you get the idea). If you posted these same 100 messages to SNS, however, 100 Lambda functions would spin up, unnecessarily increasing costs and using up your Lambda concurrency.
However, if you are still running traditional servers (like EC2 instances), you will still need to poll for messages and manage them manually.
You also have FIFO SQS queues, which guarantee the delivery order of the messages. SQS FIFO is also supported as an event source for Lambda as of November 2019
Even though there's some overlap in their use cases, both SQS and SNS have their own spotlight.
Use SNS if:
- multiple subscribers is a requirement
- sending SMS/E-mail out of the box is handy
Use SQS if:
- only one subscriber is needed
- batching is important
AWS SNS is a publisher subscriber network, where subscribers can subscribe to topics and will receive messages whenever a publisher publishes to that topic.
AWS SQS is a queue service, which stores messages in a queue. SQS cannot deliver any messages, where an external service (lambda, EC2, etc.) is needed to poll SQS and grab messages from SQS.
SNS and SQS can be used together for multiple reasons.
There may be different kinds of subscribers where some need the immediate delivery of messages, where some would require the message to persist, for later usage via polling. See this link.
The "Fanout Pattern." This is for the asynchronous processing of messages. When a message is published to SNS, it can distribute it to multiple SQS queues in parallel. This can be great when loading thumbnails in an application in parallel, when images are being published. See this link.
Persistent storage. When a service that is going to process a message is not reliable. In a case like this, if SNS pushes a notification to a Service, and that service is unavailable, then the notification will be lost. Therefore we can use SQS as a persistent storage and then process it afterwards.
From the AWS documentation:
Amazon SNS allows applications to send time-critical messages to multiple subscribers through a “push” mechanism, eliminating the need to periodically check or “poll” for updates.
Amazon SQS is a message queue service used by distributed applications to exchange messages through a polling model, and can be used to decouple sending and receiving components—without requiring each component to be concurrently available.
Following are the major differences between the main messaging technologies on AWS (SQS, SNS, +EventBridge). In order to choose a particular AWS service, we should know the functionalities a service provides as well as its comparison with other services.
The below diagram summarizes the main similarities as well as differences between this service.
In simple terms,
SNS - sends messages to the subscriber using push mechanism and no need of pull.
SQS - it is a message queue service used by distributed applications to exchange messages through a polling model, and can be used to decouple sending and receiving components.
A common pattern is to use SNS to publish messages to Amazon SQS queues to reliably send messages to one or many system components asynchronously.
Reference from Amazon SNS FAQs.
visibilityTimeout
is set, than no other systems will be able to consume the message once it's being processed by other system. –
Monicamonie There are some key distinctions between SNS and SQS:
SNS supports A2A and A2P communication, while SQS supports only A2A communication.
SNS is a pub/sub system, while SQS is a queuing system. You'd typically use SNS to send the same message to multiple consumers via topics. In comparison, in most scenarios, each message in an SQS queue is processed by only one consumer. With SQS, messages are delivered through a long polling (pull) mechanism, while SNS uses a push mechanism to immediately deliver messages to subscribed endpoints.
SNS is typically used for applications that need real time notifications, while SQS is more suited for message processing use cases.
SNS does not persist messages - it delivers them to subscribers that are present, and then deletes them. In comparison, SQS can persist messages (from 1 minute to 14 days).
Individually, Amazon SQS and SNS are used for different use cases. You can, however, use them together in some scenarios.
One reason for coupling SQS and SNS would be for data processing pipelines.
Let's say you are generating three kinds of product, and that products B & C are both derived from the same intermediate product A. For each kind of product (i.e., for each segment of the pipeline) you set up:
- a compute resource (maybe a lambda function, or a cluster of virtual machines, or an autoscaling kubernetes job) to generate the product.
- a queue (describing units of work that need to be performed) to partition the work across the compute resource (so that each unit of work is processed exactly once, but separate units of work can be processed separately in parallel and asynchronously with each other).
- a news feed (announcing outputs that have been produced).
Then arrange so that the input queues for B & C are both subscribing to the output announcements of A.
This makes the pipeline modular on the level of infrastructure. Rather than having a monolithic server application that generates all three products together, different stages of the pipeline can utilise different hardware resources (for example, perhaps stage B is very memory intensive, but the two other stages can be performed with cheaper hardware/services). This also makes it easier to iterate on the development of one pipeline segment without disrupting delivery of the other products.
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