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 respond instantly instead of having to wait until all your data is collected before the processing can begin.
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.
Amazon Kinesis capabilities
How it works
Amazon Kinesis Video Streams
Amazon Kinesis Data Streams
Amazon Kinesis Data Firehose
Amazon Kinesis Data Analytics
Build video analytics applications
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.
Veritone Inc. (NASDAQ: VERI), a leading artificial intelligence (AI) and cognitive solutions provider, combines a powerful suite of applications with over 120 best-in-class cognitive engines including facial and object recognition, transcription, geolocation, sentiment detection, and translation. With Amazon Kinesis Video Streams, customers can easily stream their content to AWS, where Veritone processes and enriches their content with AI, in near real-time and at scale. Within seconds of capture, Kinesis Video Streams and Veritone make every frame of video or second of audio searchable for objects, faces, brands, keywords and more.
Evolve from Batch to Real-time Analytics
With Amazon Kinesis, you can perform real-time analytics on data that has been traditionally analyzed using batch processing in data warehouses or using Hadoop frameworks. The most common use cases include data lakes, data science and machine learning. You can use Kinesis Firehose to continuously load streaming data into your S3 data lakes. You can also update machine learning models more frequently as new data becomes available, ensuring accuracy and reliability of the outputs. Try a hands-on tutorial »
Zillow uses Kinesis Streams to collect public record data and MLS listings, and then update home value estimates in near real-time so home buyers and sellers can get the most up to date home value estimates. Zillow also sends the same data to its S3 data lake using Kinesis Firehose, so that all the applications can work with the most recent information. Read the case study »
Build Real-time Applications
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 Streams, process it using Kinesis Analytics, and emit the results to any data store or application using Kinesis 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. For more information, read this whitepaper »
Netflix uses Amazon Kinesis to monitor the communications between all of its applications so it can detect and fix issues quickly, ensuring high service uptime and availability to its customers. Read the case study »
Analyze IoT Device Data
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. Download sample code »