What is the difference/use case for Kinesis services of Firehose, pipeline, data stream

Question

I am confused on the different Kinesis services, I've read the following terms:

Kinesis streaming data platform
Kinesis Data Stream
Kinesis Data Firehose
Kinesis Video Stream
Kinesis Data Analytics
Kinesis Data Pipeline

Can any one shed me with some lights on what is each of the services or maybe just a nickname? what are their use cases?

Thanks.

Answer 1

There are 4 flavors of Kinesis. Some of the other ones you've presented seem to be aliases, yes. You can confirm this under "Amazon Kinesis capabilities" at https://aws.amazon.com/kinesis/ . I've pulled the descriptions from the FAQs.

Data Streams: Amazon Kinesis Data Streams enables you to build custom applications that process or analyze streaming data for specialized needs.

Data Analytics: Amazon Kinesis Data Analytics is the easiest way to analyze streaming data, gain actionable insights, and respond to your business and customer needs in real time. (TL;DR, you can process data, in near-realtime using SQL application code)

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.

Data Firehose: Amazon Kinesis Data Firehose is the easiest way to load streaming data into data stores and analytics tools. It can capture, transform, and load streaming data into Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, and Splunk, enabling near real-time analytics with existing business intelligence tools and dashboards you're already using today.

Firehose and Data Streams are very similar. Biggest difference is Firehose will scale for you, where Data Streams gives you control on the number of "shards" your stream has. Shards control how much throughput your stream gets.