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On the role of Distinguished Engineer and CTO Mindset Apr 27, 2025 The future is bright Mar 30, 2025 On luck and gumption Oct 8, 2023 Some thoughts on recent RTO announcements Jun 22, 2023 One size does not fit all: neither cloud nor on-prem Apr 10, 2023 Comparing AWS SQS, SNS, and Kinesis: A Technical Breakdown for Enterprise Developers Feb 11, 2023 Working from home works as well as any distributed team Nov 25, 2022 Things to be Thankful for Nov 24, 2022 Why you should question the “database per service” pattern Oct 5, 2022 Stop Shakespearizing Sep 16, 2022 Using GNU Make with JavaScript and Node.js to build AWS Lambda functions Sep 4, 2022 Why don’t they tell you that in the instructions? Aug 31, 2022 Monolithic repository vs a monolith Aug 23, 2022 Keep your caching simple and inexpensive Jun 12, 2022 Java is no longer relevant May 29, 2022 There is no such thing as one grand unified full-stack programming language May 27, 2022 Peloton could monetize these ideas if they only listen May 15, 2022 Best practices for building a microservice architecture Apr 25, 2022 True identity verification should require a human Mar 16, 2020 The passwords are no longer a necessity. Let’s find a good alternative. Mar 2, 2020 What programming language to use for a brand new project? Feb 18, 2020 TDWI 2019: Architecting Modern Big Data API Ecosystems May 30, 2019 Configuring Peloton Apple Health integration Feb 16, 2019 All emails are free -- except they are not Feb 9, 2019 Using Markov Chain Generator to create Donald Trump's state of union speech Jan 20, 2019 The religion of JavaScript Nov 26, 2018 Teleportation can corrupt your data Sep 29, 2018 Let’s talk cloud neutrality Sep 17, 2018 A conservative version of Facebook? Aug 30, 2018 On Facebook and Twitter censorship Aug 20, 2018 Facebook is the new Microsoft Apr 14, 2018 Node.js is a perfect enterprise application platform Jul 30, 2017 Design patterns in TypeScript: Factory Jul 30, 2017 Design patterns in TypeScript: Chain of Responsibility Jul 22, 2017 Singletons in TypeScript Jul 16, 2017 Architecting API ecosystems: my interview with Anthony Brovchenko of R. Culturi Jun 5, 2017 TDWI 2017, Chicago, IL: Architecting Modern Big Data API Ecosystems May 30, 2017 I tried an Apple Watch for two days and I hated it Mar 30, 2017 Emails, politics, and common sense Jan 14, 2017 Online grocers have an additional burden to be reliable Jan 5, 2017 Here is to a great 2017! Dec 26, 2016 Apple’s recent announcements have been underwhelming Oct 29, 2016 I am addicted to Medium, and I am tempted to move my entire blog to it Sep 9, 2016 What I learned from using Amazon Alexa for a month Sep 7, 2016 Praising Bank of America's automated phone-based customer service Aug 23, 2016 Amazon Alexa is eating the retailers alive Jun 22, 2016 In search for the mythical neutrality among top-tier public cloud providers Jun 18, 2016 In Support Of Gary Johnson Jun 13, 2016 Files and folders: apps vs documents May 26, 2016 Why it makes perfect sense for Dropbox to leave AWS May 7, 2016 JEE in the cloud era: building application servers Apr 22, 2016 Managed IT is not the future of the cloud Apr 9, 2016 LinkedIn needs a reset Feb 13, 2016 In memory of Ed Yourdon Jan 23, 2016 OAuth 2.0: the protocol at the center of the universe Jan 1, 2016 IT departments must transform in the face of the cloud revolution Nov 9, 2015 Banking Technology is in Dire Need of Standartization and Openness Sep 28, 2015 Top Ten Differences Between ActiveMQ and Amazon SQS Sep 5, 2015 We Live in a Mobile Device Notification Hell Aug 22, 2015 On Maintaining Personal Brand as a Software Engineer Aug 2, 2015 Book Review: "Shop Class As Soulcraft" By Matthew B. Crawford Jul 5, 2015 Attracting STEM Graduates to Traditional Enterprise IT Jul 4, 2015 The longer the chain of responsibility the less likely there is anyone in the hierarchy who can actually accept it Jun 7, 2015 Guaranteeing Delivery of Messages with AWS SQS May 9, 2015 The Clarkson School Class of 2015 Commencement speech May 5, 2015 Apple is (or was) the Biggest User of Apache Cassandra Apr 23, 2015 Ordered Sets and Logs in Cassandra vs SQL Apr 8, 2015 Exploration of the Software Engineering as a Profession Apr 8, 2015 What can Evernote Teach Us About Enterprise App Architecture Apr 2, 2015 Microsoft and Apple Have Everything to Lose if Chromebooks Succeed Mar 31, 2015 Where AWS Elastic BeanStalk Could be Better Mar 3, 2015 Configuring Master-Slave Replication With PostgreSQL Jan 31, 2015 Docker can fundamentally change how you think of server deployments Aug 26, 2014 Infrastructure in the cloud vs on-premise Aug 25, 2014 Things I wish Apache Cassandra was better at Feb 12, 2014 "Hello, World!" Using Apache Thrift Feb 24, 2013 Thoughts on Wall Street Technology Aug 11, 2012 Scripting News: After X years programming Jun 5, 2012 Java, Linux and UNIX: How much things have progressed Dec 7, 2010

Comparing AWS SQS, SNS, and Kinesis: A Technical Breakdown for Enterprise Developers

February 11, 2023

Queuing is a critical component of software architecture, and choosing the right system for your cloud-native enterprise application is crucial. In this blog post, we'll compare Amazon Simple Queue Service(SQS), Amazon Simple Notification Service (SNS), and Amazon Kinesis, exploring their strengths and weaknesses to help you determine which queuing system is best suited for your use case. 




Some background




Queuing is a fundamental aspect of software architecture that enables applications to manage incoming requests and prioritize tasks. It acts as a buffer between the application and its clients, allowing the application to process requests in an orderly and efficient manner. Queues can significantly improve performance, reliability, and scalability, especially in high-traffic or resource-intensive environments.



There are several types of queuing systems, including message queues, task queues, and event-driven queues. Message queues allow applications to exchange messages with each other, while task queues prioritize and manage long-running tasks. Event-driven queues allow applications to react to events in real time. Each type of queuing system has its use cases and benefits, and choosing the right one for your application depends on your specific requirements. Understanding the importance of queuing and its different types is essential for building a robust and scalable software architecture.




Amazon SQS




Amazon Simple Queue Service (SQS) is a highly scalable, fully managed message queuing service offered by AWS. It provides a distributed message queue for decoupling the components of a cloud-native enterprise application. With SQS, you can send, store, and receive messages between services, enabling asynchronous communication and helping to ensure that your application remains highly available and responsive.



SQS offers several key features, including support for standard and FIFO queues, the ability to send and receive an unlimited number of messages, and automatic scaling to handle changes in traffic. It also guarantees durability, ensuring that messages are stored redundantly across multiple availability zones. SQS can help you build scalable, reliable, and cost-effective cloud-native enterprise applications with these features. 




Amazon SNS




Amazon Simple Notification Service (SNS) is a flexible publish-subscribe messaging service offered by AWS. SNS enables you to send messages to multiple subscribers, including other AWS services, HTTP/S endpoints, email addresses, and mobile devices, allowing you to build applications that react to events in real time. SNS is often used in conjunction with other AWS services to build event-driven architectures, where components of an application can respond to changes in the environment in real time.



SNS offers support for multiple message formats, the ability to publish messages to multiple subscribers, and automatic retries in the event of delivery failures. It also guarantees durability, ensuring that messages are stored redundantly across multiple availability zones. SNS is an ideal solution for building highly scalable, reliable, and cost-effective cloud-native enterprise applications that require real-time event-driven processing. 




Amazon Kinesis




Kinesis allows you to collect, process, and analyze real-time data streams from multiple sources, including IoT devices, mobile apps, website clickstreams, and logs. Kinesis provides a real-time data processing platform that enables you to process and analyze large amounts of data in real time, making it an ideal solution for building real-time data-driven applications.



Kinesis supports real-time data processing, automatic scaling to handle changes in traffic, and the ability to handle millions of events per second. It also guarantees durability, ensuring data is stored redundantly across multiple availability zones. Kinesis is an ideal solution for building highly scalable, reliable, and cost-effective cloud-native enterprise applications that require real-time data processing and analysis. 




Side-by-side comparison of SQS, SNS and Kinesis: top 10





SQSSNSKinesis
PurposeA message queue service for decoupling components of an applicationA publish-subscribe messaging service for real-time event-driven processingA data streaming service for real-time data processing and analysis
Maximum message size256 KB256 KB for SMS, 2 KB for all others1 MB
Delivery guaranteeAt least onceBest effortOrdered, real-time
OrderingFIFO (best effort for standard)No guaranteeFIFO
Visibility timeoutUp to 12 hoursNoneNone
RetriesAutomated retries, configurableAutomated retriesNo retries, requires coding
SubscribersOne subscriberMultiple subscriberOne subscriber
Data retentionUp to 14 daysNoneUp to 24 hours, configurable up to 1 year
Realtime processingAsynchronousRealtimeRealtime
CostCheap for most use caseExpensive for high frequency useCan get expensive when processing large amounts of data




Integration and interoperability




Integration and interoperability are important considerations when choosing a queuing system for your cloud-native enterprise application. Integrating with other AWS services and external systems can significantly enhance the functionality and efficiency of your application. It is essential to carefully evaluate your requirements and consider the available options for integrating and interoperating with other systems.



Amazon Simple Queue Service (SQS), Amazon Simple Notification Service (SNS), and Amazon Kinesis can all be integrated with other AWS services and external systems. For example, SQS can be integrated with Amazon Lambda to trigger serverless functions in response to messages in a queue. SNS can be integrated with Amazon SES to send email notifications, and Kinesis can be integrated with Amazon Redshift for real-time data analysis. These integrations can be accomplished using the AWS Management Console, APIs, and SDKs. Additionally, all three services can be integrated with external systems using the HTTP/S protocol, enabling you to build complex, multi-tier architectures that span multiple cloud and on-premises environments.




Some final thoughts




In conclusion, choosing the right queuing system for your cloud-native enterprise application can significantly enhance your application's functionality, reliability, and performance. Amazon Simple Queue Service (SQS), Amazon Simple Notification Service (SNS), and Amazon Kinesis are all highly scalable, fully managed, and flexible queuing systems offered by AWS. SQS is a message queue service for decoupling components of an application, SNS is a publish-subscribe messaging service for real-time event-driven processing, and Kinesis is a data streaming service for real-time data processing and analysis. When deciding which queuing system to use, it is important to carefully evaluate your requirements, consider the available options for integration and interoperability, and choose the solution that best fits your needs.