AWS SQS vs AWS SNS vs AWS KINESIS | AWS Recap
Let's do a recap for the topics where we can introspect on the difference between AWS SQS, AWS SNS, and AWS KINESIS
AWS KINESIS: https://youtu.be/ZW6wbUILlI0
Kinesis Video Streams
Amazon Kinesis Video Streams makes it easy to securely stream video from connected devices to AWS for analytics, machine learning (ML), and other processing. When you read video steaming for analytics, think of KVS
Kinesis Data Streams
Amazon Kinesis Data Streams is a scalable and durable real-time data streaming service that can continuously capture gigabytes of data per second from hundreds of thousands of sources.
Kinesis Data Firehose
Amazon Kinesis Data Firehose is the easiest way to capture, transform, and load data streams into AWS data stores for near real-time analytics with existing business intelligence tools.
Kinesis Data Analytics
Amazon Kinesis Data Analytics is the easiest way to process data streams in real-time with SQL or Java without having to learn new programming languages or processing frameworks.
AWS SNS: https://youtu.be/WtaXItB_aqo
Amazon Simple Notification Service (SNS) is a highly available, durable, secure, fully managed pub/sub messaging service that enables you to decouple microservices, distributed systems, and serverless applications
Amazon SNS provides topics for high-throughput, push-based, many-to-many messaging. So just think of what we learned in the previous slide, Here SNS provide topics as we discussed, for high throughput and there can be many Publishers and Many Subscribers, and Each SNS can have multiple topics for the consumers or the services that we want to serve.
AWS SQS: https://youtu.be/_gpOHGnoq_o
Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications.
Here as well, just like Message queue, we have our Producers who actually have messages that they want to be processed and we have our consumers who are waiting to process these messages.
And to propagate these messages, in AWS we make us of AWS SQS aka Simple Queue Service.
Producers push these messages or tasks to the AWS SQS queues for them to be executed with the consumers at hand.
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Disclaimer: The content provided in the channel are not affiliated in any way to the organization. We provide information here on the channel based on the knowledge we have on the topic. We advise our viewers to please do their own research and read more about them from the source provided by the organization to get a better outlook on the topic that has been covered.
These videos are just to provide you a platform to learn, and there can be mistakes and we are always trying to improve based on your feedback. we recommend viewers to have an open mind. Please support the channel to get more content like these in the future.
#RoadToAWS #AWSSolutionsArchitectAssociate2020 #Pythoholic
Видео AWS SQS vs AWS SNS vs AWS KINESIS | AWS Recap канала Pythoholic
AWS KINESIS: https://youtu.be/ZW6wbUILlI0
Kinesis Video Streams
Amazon Kinesis Video Streams makes it easy to securely stream video from connected devices to AWS for analytics, machine learning (ML), and other processing. When you read video steaming for analytics, think of KVS
Kinesis Data Streams
Amazon Kinesis Data Streams is a scalable and durable real-time data streaming service that can continuously capture gigabytes of data per second from hundreds of thousands of sources.
Kinesis Data Firehose
Amazon Kinesis Data Firehose is the easiest way to capture, transform, and load data streams into AWS data stores for near real-time analytics with existing business intelligence tools.
Kinesis Data Analytics
Amazon Kinesis Data Analytics is the easiest way to process data streams in real-time with SQL or Java without having to learn new programming languages or processing frameworks.
AWS SNS: https://youtu.be/WtaXItB_aqo
Amazon Simple Notification Service (SNS) is a highly available, durable, secure, fully managed pub/sub messaging service that enables you to decouple microservices, distributed systems, and serverless applications
Amazon SNS provides topics for high-throughput, push-based, many-to-many messaging. So just think of what we learned in the previous slide, Here SNS provide topics as we discussed, for high throughput and there can be many Publishers and Many Subscribers, and Each SNS can have multiple topics for the consumers or the services that we want to serve.
AWS SQS: https://youtu.be/_gpOHGnoq_o
Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications.
Here as well, just like Message queue, we have our Producers who actually have messages that they want to be processed and we have our consumers who are waiting to process these messages.
And to propagate these messages, in AWS we make us of AWS SQS aka Simple Queue Service.
Producers push these messages or tasks to the AWS SQS queues for them to be executed with the consumers at hand.
Please follow we in the links below to stay updated: 🙌
🍀Click on the link below to subscribe: https://tinyurl.com/qqebnwz
🍀Instagram: https://www.instagram.com/tougherapollo/
🍀Twitter: https://twitter.com/TougherApollo1
🍀Discord: https://discord.gg/dsZ6Wdh
Disclaimer: The content provided in the channel are not affiliated in any way to the organization. We provide information here on the channel based on the knowledge we have on the topic. We advise our viewers to please do their own research and read more about them from the source provided by the organization to get a better outlook on the topic that has been covered.
These videos are just to provide you a platform to learn, and there can be mistakes and we are always trying to improve based on your feedback. we recommend viewers to have an open mind. Please support the channel to get more content like these in the future.
#RoadToAWS #AWSSolutionsArchitectAssociate2020 #Pythoholic
Видео AWS SQS vs AWS SNS vs AWS KINESIS | AWS Recap канала Pythoholic
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