Amazon Kinesis vs. AWS IoT Core

Perfect for real-time data processing and streaming. Also, there's no need for any specific setup - you just start using it immediately and it easily integrates with the rest of AWS capabilities (like Redshift), although integration with Lambda could be better. You can make your overall analytics landscape way simpler with Kineses even if you have non-Amazon solutions like Tableau. It all integrates really well!

Incentivized

AWS iot core is very useful if you need to scale very quickly for managing lots of devices without handling the underlying infrastructure cost. It can enable real time publishing and subscription of devices, monitoring and early stage intervention in case of unexpected issues while developing a full stack solution. However, healthcare scenarios where government intervention is needed should be developed and scaled by following the set of compliance policies of the government and the SLA requirements of the customer. Finally, it is great where you need to do data science research after anonymizing data

Incentivized

• Integrating with other Amazon services
• Scaling requests
• Totally serverless platform
• Simple management

Incentivized

• AWS IoT Core integrates power analytics and an AI solution for sensor data processing.
• Great protocol support including HTTPs and MQTT required to connect resource constraint IoT devices to cloud
• High security standards during data transmission
• Scalability and a great user community

Incentivized

• Improve integration with AWS Lambda
• Some duplicate records coming from the stream

Incentivized

• It would be great to have better integration with other IoT products outside of AWS
• It has been lagging in some of our applications. It's difficult to tell whether this is on AWS IoT or on our implementation
• It would be great to support a wider range of protocols

Incentivized

I give AWS IoT Core's overall usability this rating because it is very easy to use and is enjoyed by all of our staff. The only problem is that it sometimes glitches and it freezes a lot. So overall, the usability of AWS IoT Core is very good, and we will continue to use it.

Incentivized

The documentation was confusing and lacked examples. The streams suddenly stopped working with no explanation and there was no information in the logs. All these were more difficult when dealing with enhanced fan-out. In fact, we were about to abort the usage of Kinesis due to a misunderstanding with enhanced fan-out.

Incentivized

It covers all the aspects of IoT services required for an IoT company. It supports all the industry-wide protocols for secure data transmission and integrates powerful AL and ML technology for data analytics. For data storage, Amazon S3 is a great solution. Strong tech support and user community. Since it is widely used as compared to other products, there is an abundance of training and learning material on the web.

Incentivized

Kinesis is oriented to streaming in a scalable way large volumes of information in real-time. Glue is more an ETL so it is not well suited for real-time applications while Beanstalk is more a simple container platform. Lambda could do the job but it would require a lot of programming to accomplish the same as Kinesis. In fact, our solution employed the four elements for different tasks but using Kinesis as the message bus.

Incentivized

Azure IoT is a good product but since our whole suite of tech is now set up in AWS (ec2, s3, sagemaker, cloud formation, etc.), we wanted something that could quickly adapt to our environments. Learning a new tech for IoT was simply a bottleneck that we wanted to avoid at this point.

Incentivized

• Caused us to need to re-engineer some basic re-try logic
• Caused us to drop some content without knowing it
• Made monitoring much more difficult
• We eventually switched back to SQS because Kinesis is not the same as a Queue system

Incentivized

• Gives confidence to prototype iot solutions across lots of devices in little time
• Ability to meet requirements for managing a variety of communication protocols
• Learning iot analytics and visualization for faster insights enablement
• Onboarding devices and managing quickly without building inhouse solutions

Incentivized