Last updated 21/07/2021
Amazon Kinesis is a managed, scalable, cloud-based service that allows real-time processing of streaming large amounts of data per second. It is designed for real-time applications and allows developers to take in any amount of data from several sources, scaling up and down that can be run on EC2 instances.
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and responds instantly instead of having to wait until all your data is collected before the processing can begin.
There are four major capabilities of Amazon Kinesis, let’s understand them one by one
Amazon Kinesis Video Streams makes it easy to securely stream video from connected devices to AWS for analytics, machine learning (ML), playback, and other processing. Kinesis Video Streams automatically provisions and elastically scales all the infrastructure needed to ingest streaming video data from millions of devices. It durably stores, encrypts, and indexes video data in your streams, and allows you to access your data through easy-to-use APIs. Kinesis Video Streams enables you to playback video for live and on-demand viewing, and quickly build applications that take advantage of computer vision and video analytics through integration with Amazon Rekognition Video, and libraries for ML frameworks such as Apache MxNet, TensorFlow, and OpenCV. Kinesis Video Streams also supports WebRTC, an open-source project that enables real-time media streaming and interaction between web browsers, mobile applications, and connected devices via simple APIs. Typical uses include video chat and peer-to-peer media streaming.
Amazon Kinesis Video Streams provides SDKs that make it easy for devices to securely stream media to AWS for playback, storage, analytics, machine learning, and other processing.
Easily build applications with real-time computer vision capabilities through integration with Amazon Rekognition Video, and with real-time video analytics capabilities using popular open-source machine learning frameworks.
Easily stream live and recorded media from your Kinesis video streams to your browser or mobile application using the Kinesis Video Streams HTTP Live Streaming (HLS) capability.
Amazon Kinesis Video Streams supports the open-source project WebRTC for two-way, real-time media streaming between web browsers, mobile applications, and connected devices. With support for WebRTC, you can use simple APIs to build rich applications like video chat and peer-to-peer data sharing with ultra-low latency and two-way communication between your applications and connected devices.
Amazon Kinesis Video Streams allows you to control access to your streams using AWS Identity and Access Management (IAM). It helps you protect your data by automatically encrypting the data at rest using AWS Key Management Service (KMS) and in transit using the industry-standard Transport Layer Security (TLS) protocol.
Amazon Kinesis Video Streams uses Amazon S3 as the underlying data store, which means your data is stored durably and reliably. Kinesis Video Streams enables you to quickly search and retrieve video fragments based on device and service-generated timestamps.
Amazon Kinesis Video Streams manages all the infrastructure for you. You don’t have to worry about configuration, software updates, failures, or scaling infrastructure as the number of streams and consuming applications grows. Kinesis Video Streams handles all the administration and maintenance required to manage your streams, so you can focus your time on building innovative applications.
Amazon Kinesis Data Streams (KDS) is a massively scalable and durable real-time data streaming service. KDS can continuously capture gigabytes of data per second from hundreds of thousands of sources such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, and location-tracking events. The data collected is available in milliseconds to enable real-time analytics use cases such as real-time dashboards, real-time anomaly detection, dynamic pricing, and more.
Make your streaming data available to multiple real-time analytics applications, to Amazon S3, or AWS Lambda within 70 milliseconds of the data being collected.
Reduce the probability of data loss. Synchronous replication of your streaming data across three Availability Zones in an AWS Region and store that data for up to 365 days to provide multiple layers of protection from data loss.
Meet your regulatory and compliance needs by encrypting sensitive data within KDS, and privately accessing your data via your Amazon Virtual Private Cloud (VPC). Data can be secured at-rest by using server-side encryption and AWS KMS master keys.
Build your streaming applications quickly using the AWS SDK, the Kinesis Client Library (KCL), connectors, and agents. Easily process data with built-in integrations to AWS Lambda, Amazon Kinesis Data Analytics, Amazon Kinesis Data Firehose, and AWS Glue Schema Registry.
Dynamically scale your applications. Kinesis data streams scale from megabytes to terabytes per hour and scale from thousands to millions of PUT records per second. You can dynamically adjust the throughput of your stream at any time based on the volume of your input data.
Kinesis Data Streams has no upfront cost, and you only pay for the resources you use. For as little as $0.015 per hour, you can have a Kinesis data stream with 1MB/second ingest and 2MB/second egress capacity.
Amazon Kinesis Data Firehose is the easiest way to reliably load streaming data into data lakes, data stores, and analytics services. It can capture, transform, and deliver streaming data to Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, generic HTTP endpoints, and service providers like Datadog, New Relic, MongoDB, and Splunk. It is a fully managed service that automatically scales to match the throughput of your data and requires no ongoing administration. It can also batch, compress, transform, and encrypt your data streams before loading, minimizing the amount of storage used and increasing security.
Amazon Kinesis Data Firehose provides a simple way to capture, transform, and load streaming data with just a few clicks in the AWS Management Console. You can quickly create a Firehose delivery stream, select the destinations, and start sending real-time data from hundreds of thousands of data sources simultaneously. The service takes care of stream management, including all the scaling, sharding, and monitoring needed to continuously load the data to destinations at the intervals you specify.
Amazon Kinesis Data Firehose is integrated with Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service. It can also deliver data to generic HTTP endpoints and directly to service providers like Datadog, New Relic, MongoDB, and Splunk. From the AWS Management Console, you can point Kinesis Data Firehose to the destinations of your choice and use your existing applications and tools to analyze streaming data.
Amazon Kinesis Data Firehose enables you to prepare your streaming data before it is loaded to data stores. With Kinesis Data Firehose, you can easily convert raw streaming data from your data sources into formats like Apache Parquet and Apache ORC required by your destination data stores, without having to build your own data processing pipelines.
Amazon Kinesis Data Firehose captures and loads data in near real-time. It loads new data into your destinations within 60 seconds after the data is sent to the service. As a result, you can access new data sooner and react to business and operational events faster.
Amazon Kinesis Data Firehose is a fully managed service that automatically provisions, manages, and scales compute memory, and network resources required to process and load your streaming data. Once set up, Kinesis Data Firehose loads data streams into your destinations continuously as they arrive.
With Amazon Kinesis Data Firehose, you pay only for the volume of data you transmit through the service, and if applicable, for data format conversion. You also pay for Amazon VPC delivery and data transfer when applicable. There are no minimum fees or upfront commitments.
Amazon Kinesis Data Analytics is the easiest way to transform and analyze streaming data in real-time with Apache Flink. Apache Flink is an open-source framework and engine for processing data streams. Amazon Kinesis Data Analytics reduces the complexity of the building, managing, and integrating Apache Flink applications with other AWS services.
Amazon Kinesis Data Analytics takes care of everything required to run streaming applications continuously and scales automatically to match the volume and throughput of your incoming data. With Amazon Kinesis Data Analytics, there are no servers to manage, no minimum fee or setup cost, and you only pay for the resources your streaming applications consume.
Amazon Kinesis Data Analytics provides built-in functions to filter, aggregate, and transform streaming data for advanced analytics. It processes streaming data with sub-second latencies, enabling you to analyze and respond to incoming data and events in real-time.
Amazon Kinesis Data Analytics is serverless; there are no servers to manage. It runs your streaming applications without requiring you to provision or manages any infrastructure. Amazon Kinesis Data Analytics automatically scales the infrastructure up and down as required to process incoming data.
With Amazon Kinesis Data Analytics, you only pay for the processing resources that your streaming applications use. There are no minimum fees or upfront commitments.
Amazon Kinesis Data Analytics enables you to easily and quickly build queries and sophisticated streaming applications in three simple steps: setup your streaming data sources, write your queries or streaming applications and set up your destination for processed data.
Amazon Kinesis enables you to ingest, buffer, and process streaming data in real-time, so you can derive insights in seconds or minutes instead of hours or days.
Amazon Kinesis is fully managed and runs your streaming applications without requiring you to manage any infrastructure.
Amazon Kinesis can handle any amount of streaming data and process data from hundreds of thousands of sources with very low latencies.
You can use Amazon Kinesis to securely stream video from camera-equipped devices in homes, offices, factories, and public places to AWS. You can then use these video streams for video playback, security monitoring, face detection, machine learning, and other analytics.
With Amazon Kinesis, you can perform real-time analytics on data that has been traditionally analyzed using batch processing. Common streaming use cases include sharing data between different applications, streaming extract-transform-load, and real-time analytics. For example, you can use Kinesis Data Firehose to continuously load streaming data into your S3 data lake or analytics services.
You can use Amazon Kinesis for real-time applications such as application monitoring, fraud detection, and live leader-boards. You can ingest streaming data using Kinesis Data Streams, process it using Kinesis Data Analytics, and emit the results to any data store or application using Kinesis Data Streams with millisecond end-to-end latency. This can help you learn about what your customers, applications, and products are doing right now and react promptly.
You can use Amazon Kinesis to process streaming data from IoT devices such as consumer appliances, embedded sensors, and TV set-top boxes. You can then use the data to send real-time alerts or take other actions programmatically when a sensor exceeds certain operating thresholds. Use our sample IoT analytics code to build your application. No need to start from scratch.
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