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What is Amazon Kinesis?

AWS Kinesis allows you to process and analyze data as it arrives and respond instantaneously, rather than having to wait for all of your data to be collected before you can begin processing.

For machine learning, analytics, and other applications, you may use Amazon Kinesis to ingest real-time data like video, audio, application logs, website clickstreams, and IoT telemetry data.

In this article, we will be discussing the following terms related to AWS Kinesis:

Watch this AWS Kinesis Tutorial for a more practical understanding:

Amazon Kinesis Components

Let’s talk about 4 major AWS Kinesis Components:

Amazon Kinesis Video Stream:

Amazon Kinesis Video Streams enables customers to securely stream movies from AWS-connected devices for machine learning (ML), analytics, playback, and other processing purposes. Kinesis Video Streams automatically provision and elastically scale all infrastructure required to ingest streaming video data from different devices.

Kinesis Video Streams provides access to video data with simple APIs while securely encrypting, indexing, storing, and storing the data in streams. It also aid in the processing and storage of media, as well as the recording of streams for analytics, machine learning, and playback.

Amazon Kinesis Video Stream


Data from edge devices, cellphones, security cameras, and other data sources including RADARs, LIDARs, drones, satellites, dash cams, and depth sensors can all be processed by Kinesis Video Streams.

Amazon Kinesis Data Streams

Kinesis Data Streams can be used for continuous and quick data intake & aggregation. Data from social media, market data feeds, IT infrastructure logs, application logs, and web clickstreams are a few examples of the types of data that can be used. Because the response time for data intake and processing occurs in real-time, overall processing is often lightweight.

Amazon Kinesis Data Streams

Few use cases for Kinesis Data Streams include:

Real-time metrics and reporting – Data gathered in Kinesis Data Streams can be used for easy real-time data analysis and reporting. For eg., Instead of waiting for batches of data to arrive, your data-processing application can work on metrics and report for system and application logs as the data is flowing in.

Real-time data analytics – Through this, real-time data and the strength of parallel processing are combined. You could, for instance, use several consecutive Kinesis Data Streams applications to process website clickstreams in real-time and subsequently assess user engagement with the site.

Accelerated log and data feed intake and processing – Producers can immediately push data into a stream. Push system and application logs, for example, and they will be ready for processing in seconds. By doing this, the log data is kept intact even if the front end or application servers crash. Because you do not batch the data on the servers before submitting it for intake, Kinesis Data Streams delivers quicker data feed intake.

Complex stream processing – Kinesis Data Streams apps and data streams can be used to generate Directed Acyclic Graphs (DAGs). This often involves transferring data from numerous Kinesis Data Streams applications into another stream for processing by a different Kinesis Data Streams application.

Benefits of Using Kinesis Data Streams:

Amazon Kinesis Data Firehose

Real-time streaming data can be delivered to services like Amazon S3, Amazon Redshift, Amazon ES, Splunk, and any custom HTTP endpoint owned by supported third-party service users like Datadog, MongoDB, and New Relic using Amazon Kinesis Data Firehose, a fully managed service. Along with Amazon Kinesis Data Analytics, Kinesis Data Streams, and Kinesis Video Streams, Kinesis Data Firehose is a part of the Kinesis streaming data platform. You cannot manage resources or create applications with Kinesis Data Firehose. When you set up your data producers to submit data to Kinesis Data Firehose, the data is automatically sent to the location you mentioned.

Amazon Kinesis Data Firehose

Its benefits include:

Amazon Kinesis Data Analytics

A brand-new machine learning function called Amazon Kinesis Data Analytics was just released to find “hotspots” in the streaming data. It essentially functions as a real-time processing engine that enables you to create and run SQL queries to extract useful information from the data.

It provides Kinesis Data Streams with the output or results. There is a feature called “HOTSPOTS” that improves the capabilities of current machine learning. Clients can also drag and drop unsupervised streaming-based machine learning algorithms.

Amazon Kinesis Data Analytics

Benefits include:

Interested in learning more? Go through this AWS Tutorial!

Benefits of Amazon Kinesis

If you have any doubts or queries related to AWS, do a post on AWS Community.

How to use Amazon Kinesis?

When we need continuous processing of quickly moving data, it is used. Amazon Kinesis can be useful for the following scenarios:

Amazon Kinesis Pricing

Amazon Kinesis is offered on a pay-per-use basis. This breaks downs as follows:

This varies by region. You may also use the Kinesis Data Analytics calculator to estimate the cost of the application you’re developing. Pricing can increase dramatically when you plug in other complementing services, as with most AWS services, therefore anticipate your setup before implementation to determine where savings might be realized.


Amazon Kinesis is a controlled, scalable, cloud-based system that enables the real-time processing of massive amounts of data per second. It is intended for real-time applications and enables developers to take in an unlimited amount of data from numerous sources while scaling up and down which can be run on EC2 instances.

In this blog, you learned about Amazon Kinesis, its essential features, and its various components, which include Kinesis Firehose, Kinesis Data Analytics, Kinesis Data Streams, and Kinesis Video Streams.

Start learning now by enrolling in Intellipaat’s Cloud Computing and DevOps Program

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