Cloud service · AWS

Amazon Kinesis

In short

Amazon Kinesis is a cloud-based service from Amazon Web Services that enables real-time processing of streaming data at large scale.

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7 key features of Amazon Kinesis

Amazon Kinesis is a scalable and durable real-time data streaming service that enables continuous capture, processing, and analysis of large streams of data in real time, supporting various applications like log and event data collection, real-time analytics, machine learning model inference, and more.

Real-time Data Processing

Amazon Kinesis enables users to process and analyze data as it arrives, making it possible to obtain insights and respond to information in real-time.

Scalable

Kinesis can handle any amount of streaming data and process data from hundreds of thousands of sources with very low latencies.

Easy to Use

With Amazon Kinesis, you can quickly set up and start streaming data without managing infrastructure.

Data Integration

It seamlessly integrates with other AWS services, making it easy to send data to services such as AWS Lambda, Amazon S3, Amazon Redshift, and Amazon OpenSearch Service.

Durability and Availability

Amazon Kinesis stores data in multiple facilities and on multiple devices within each facility, offering high durability and availability of your streaming data.

Flexible Data Consuming

You can build Kinesis applications using popular programming languages, and it supports multiple consumers of the same data stream, enabling complex analytical scenarios.

Security

Kinesis provides strong security and identity management via AWS Identity and Access Management (IAM), encryption in transit and at rest, and VPC endpoints for private network connectivity.

Where Amazon Kinesis is used

Amazon Kinesis facilitates real-time processing and analysis of large, streaming data sets, enabling applications such as live event monitoring, log and event data collection, real-time analytics, and machine learning model inference.

01
Real-Time Data Analytics
Amazon Kinesis is used for real-time processing and analysis of large streams of data. Businesses can gain insights into their operations, customer behavior, and market trends as data is ingested. This allows for immediate decision-making and the ability to respond to insights in real-time, optimizing operations and enhancing customer experiences.
02
Log and Event Data Collection
Kinesis can collect logs and event data from various sources, such as website clickstreams, application logs, and IoT device data. This data is then available for monitoring, analysis, and triggering of alerts or actions based on predefined criteria, improving system performance and security posture.
03
Video Stream Processing
Amazon Kinesis Video Streams enables the processing and analysis of video streams for applications such as security surveillance, live broadcasting, and video playback. This can facilitate use cases like facial recognition, object detection, and real-time video analytics.
04
Time Series Analytics
Kinesis is well-suited for time series data analysis, making it a powerful tool for financial services, IoT applications, and telemetry data analysis. Companies can track metrics over time, identify trends, and make predictions based on historical data.
05
IoT Data Processing
For IoT applications, Amazon Kinesis can ingest and process vast amounts of data from connected devices in real-time. This enables use cases such as remote device monitoring, predictive maintenance, and dynamic pricing based on current demand or environmental conditions.

How Amazon Kinesis is priced

Amazon Kinesis pricing models typically involve pay-as-you-go fees based on the volume of data ingested, stored, and processed, as well as any additional features or services used, such as data retention or shard-hour consumption.

Pay-as-you-go

Kinesis Data Streams pricing depends on its capacity mode: provisioned mode charges for shard hours and PUT payload units, while on-demand modes use usage-based pricing.

Data Transfer

Kinesis Data Streams does not charge for transfers from producers or to consuming applications when all resources are in the same AWS Region. Cross-Region writes incur standard AWS data transfer charges. Cross-Region reads incur standard AWS data transfer charges in On-demand Standard and On-demand Advantage modes, but not in provisioned mode.

On-demand Standard

Kinesis Data Streams On-demand Standard automatically manages capacity and charges for data written, data read, and a per-stream hourly fee, with additional charges for optional capabilities.

On-demand Advantage

Charges are based on data ingested and retrieved, with account-level minimum charges equivalent to 25 MB/s ingested and 25 MB/s retrieved across all on-demand streams. There is no stream-hour charge or additional enhanced fan-out charge; retention beyond 24 hours and up to one year incurs additional charges.

S3 delivery

Direct S3 delivery is charged per GB successfully delivered, with rates varying by capacity mode and no setup fees, minimum commitments, or upfront costs.

Streaming tables

Streaming tables delivery is charged per GB of uncompressed data successfully delivered, with rates varying by capacity mode and no setup fees, minimum commitments, or upfront costs.

Services Amazon Kinesis works with

AWS Lambda

Kinesis integrates with Lambda to enable real-time data processing. Lambda can be triggered by Kinesis streams to process data as it arrives, enabling applications like real-time analytics, monitoring, and ETL (Extract, Transform, Load) operations.

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Amazon S3

Kinesis Data Streams can deliver streaming data directly to general purpose Amazon S3 buckets without a separately managed delivery pipeline. This is useful for storing data for long-term retention or downstream batch analytics.

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Amazon Redshift

Amazon Data Firehose can deliver streaming data into Amazon Redshift for analytics. This integration helps in creating data warehouses that are continuously updated with the latest information.

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Amazon OpenSearch Service

Amazon Data Firehose can deliver streaming data to Amazon OpenSearch Service, enabling real-time search, visualization, and analysis of data using tools like OpenSearch Dashboards.

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Amazon DynamoDB

Kinesis can stream data to DynamoDB for real-time updates and storage. This is particularly useful for applications requiring fast and scalable key-value storage with real-time data ingestion.

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AWS Glue

Kinesis integrates with AWS Glue to automate the ETL process. You can use AWS Glue to discover, catalog, and transform streaming data from Kinesis for analysis and reporting.

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Amazon CloudWatch

Kinesis streams can be monitored using Amazon CloudWatch. CloudWatch collects and tracks metrics, collects and monitors log files, and sets alarms, providing a comprehensive monitoring solution for Kinesis data streams.

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Amazon Simple Notification Service (Amazon SNS)

Kinesis can work with SNS to send notifications based on streaming data. This integration is useful for alerting and messaging based on real-time events.

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Amazon Simple Queue Service (Amazon SQS)

Kinesis can integrate with SQS to decouple and coordinate the components of distributed applications. This allows buffering and managing data flow between producers and consumers in real-time applications.

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Amazon QuickSight

Amazon Data Firehose can deliver streaming data to Amazon S3, which Amazon QuickSight can query through supported data-source connections for visualization and business intelligence. QuickSight is not a direct Firehose delivery destination.

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What is Amazon Kinesis

3 min read

Amazon Kinesis is a powerful, cloud-based platform provided by Amazon Web Services (AWS) designed to handle massive volumes of streaming data in real time. This platform enables developers and businesses to easily collect, process, and analyze streaming data to achieve timely insights and respond quickly to new information. Amazon Kinesis is particularly useful for applications that require continuous data intake and processing, such as log and event data collection, real-time analytics, machine learning model inference, and others.

At the heart of Amazon Kinesis's capability is its ability to process and analyze high volumes of data with minimal latency. This makes it an indispensable tool in scenarios where the speed of data processing is critical, such as monitoring web application interactions, financial transactions, social media feeds, or IoT sensor outputs. The platform is inherently designed to scale, allowing it to handle not only large volumes of data but also fluctuations in data volume, ensuring that data processing is maintained in real time, regardless of spikes or dips in incoming data streams.

Amazon Kinesis offers a suite of services tailored to specific real-time data handling needs. These include Kinesis Data Streams, which allows for the building of custom, real-time applications that can process or analyze streaming data; and Kinesis Video Streams, which makes it simple to securely stream video from connected devices to AWS for analytics, machine learning, and other processing. Related services include Amazon Data Firehose, formerly Kinesis Data Firehose, for loading streaming data into data stores, and Amazon Managed Service for Apache Flink, formerly Kinesis Data Analytics for Apache Flink, for processing streaming data using Apache Flink. Kinesis Data Analytics for SQL applications was discontinued on January 27, 2026, and is no longer available for workloads.

Kinesis Data Streams defaults to On-demand Standard mode. On-demand Advantage provides additional capabilities and a different pricing model in exchange for an account-level minimum throughput commitment lasting at least 24 hours.

Kinesis Data Streams also supports provisioned mode, in which you specify the stream's shard count and increase or decrease it as needed to control capacity and data distribution.

Kinesis Data Streams' direct S3 delivery is available for streams operating in On-demand Standard and On-demand Advantage modes.

The versatility of Amazon Kinesis is one of its key advantages. It supports practically any source of streaming data, enabling businesses to gain insights from a wide array of inputs. This capability empowers organizations to make more informed decisions faster, develop responsive and adaptive applications, and ultimately, provide better services to their customers. For example, a retail company can use Amazon Kinesis to analyze customer interaction data in real-time, allowing for the personalization of offers and advertisements on the fly, significantly improving customer experience and engagement.

Amazon Kinesis is also designed with ease of use in mind. It integrates seamlessly with other AWS services, making it an attractive option for businesses already leveraging AWS for their cloud computing needs. Moreover, it offers a range of tools and connectors that facilitate the quick setup and configuration of data processing pipelines, reducing the time and effort needed to start deriving value from streaming data. In conclusion, Amazon Kinesis stands out as

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