« Kinesis » : différence entre les versions
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* log processing for machine learning | * log processing for machine learning | ||
* anomyly detection in IoT devices | * anomyly detection in IoT devices | ||
== Benefits == | |||
* fully managed service (focus on data and don't worry about the underlying system) | |||
* can handle large amount of data | |||
* can consume process and buffer data in real-time | |||
* allows production of real-time metrics and reporting |
Version du 15 mai 2024 à 15:28
Description
Allows to gather data from different sources using data stream or fire hoses, and get that data to a destination in the expected format.
Allows to collect, process and analyze data in near real-time at scale.
Kinesis data streams are used in places where an unbounded stream of data needs to worked on in real time.
And Kinesis Firehose delivery streams are used when data needs to be delivered to a storage destination, such as S3.
Common use cases
- pattern detection
- click stream analysis (who is clicking on what and when)
- log processing for machine learning
- anomyly detection in IoT devices
Benefits
- fully managed service (focus on data and don't worry about the underlying system)
- can handle large amount of data
- can consume process and buffer data in real-time
- allows production of real-time metrics and reporting