AWS has launched Amazon Kinesis service that is famous for real-time big data processing and ingestion.

What is Amazon Kinesis?

Amazon Kinesis is a significant feature of Amazon Web Services (AWS) that easily gathers or collects, processes, and analyzes video and data streams in a real-time environment.  Key offerings: This enables to gain quick timely insights as well as reaction to new information instantly. There are few key capabilities and functionalities offered by Amazon Kinesis, such as processing of streaming data cost-effectively at any scale as well as flexibility feature to opt for the tools best suit the requirements of the application.

Using Amazon Kinesis, real-time data can be ingested, such as audio, video, website clickstreams, application logs, and IoT telemetry data for artificial intelligence, machine learning, and other analytics applications. Amazon Kinesis also assists with processing and analyzing data as it reaches and responds instantly without having to wait for the entire collection of data so that the processing could begin.

What are Amazon Kinesis Data Streams?

Amazon Kinesis Streams are used to gather together and process huge streams of data records in real-time. Kinesis Data Stream Applications can be created, which are data-processing applications. These applications perform the reading from a data stream in the form of data records. They use Kinesis Client Library for these operations and can run on Amazon EC2 instances. Processed records can be sent to dashboards and can be used to generate alerts, send data to other AWS services, and dynamically change advertising and pricing strategies.

Some scenarios for implementing Kinesis Data Streams are as follows:

• Real-time data analytics:

  Parallel Processing power is combined and coordinated with the value of real-time data here. For instance, website clickstreams can be processed in real-time and analysis of site usability management using various Kinesis Data Streams executing in parallel.

• Real-time metrics and reporting:

  Data collected or gathered into Kinesis Data Streams can be used for simple data analysis and reporting in real-time. For example, Data Processing Applications working on reporting and metrics for system and application logs while data streaming.

• Complex stream processing:

  Directed Acyclic Graphs (DAGs) can be developed out of data streams and Kinesis Data Stream Applications. This includes transferring data from various Kinesis Data Stream applications to another stream for downstream processing through different Kinesis Data Streams Applications.

Merits of Data Streams

We will be discussing here some of the Merits of Data Streams. Those are as follows:

• Amazon Kinesis is fully managed, and you do not need to maintain or manage any infrastructure for running your streaming applications.
• Amazon Kinesis can manage large amounts of streaming data and process data from hundreds of thousands of sources with low latencies.
• You can consume, process, and buffer data in real-time so that you can obtain insights within no time.

Use Cases of Amazon Kinesis

Few of the real-life examples where Amazon Kinesis is being applied in various industries are:

• Building real-time applications:

  Amazon Kinesis comes into existence for various purposes such as fraud detection, live leaderboards, and application monitoring. Kinesis Data Streams can be used to ingest streaming data which can be processed further using Kinesis Data Analytics. These results are then radiated to any application or data store using Kinesis Data Streams.

• Analysis of IoT Device Data:

  Streaming data coming from IoT devices such as embedded sensors, consumer appliances, and TV set-top boxes can be processed using Amazon Kinesis. Data can be used to transmit real-time alerts or take actions when a sensor exceeds certain operating thresholds.

• Building Video Analytics Applications:

  Video can be streamed securely from camera-equipped devices at home or offices or public places to AWS using Amazon Kinesis. It will serve purposes such as security monitoring, machine learning, face detection, playback, and other various analytics.

• Evolving from Batch to Real-Time Analytics:

  Data that has been traditionally analyzed using batch processing can be performed on real-time analytics using Amazon Kinesis. Common streaming use cases involve streaming extract-transform-load, sharing data between different applications, and real-time analytics.

Explore More About Amazon Kinesis by reading the following post.

ALL YOU NEED TO KNOW ABOUT AWS KINESIS

Conclusion

Amazon Kinesis comes with extraordinary features and capabilities of supporting Kinesis Data Streams, Kinesis Video Streams, Kinesis Data Analytics, and Kinesis Data Firehose. Kinesis Data Streams are durable and scalable real-time data streaming services that can frequently abduct gigabytes and terabytes of data per second from a hundred and thousands of sources such as financial transactions, social media feeds and operating logs. Kinesis Video Streams securely streams video from connected devices to Amazon Web Services (AWS) for artificial intelligence, machine learning, or other analytics processing applications.

At SNDK Corp, we offer best cloud computing services such as AWS, Microsoft Azure and Google Cloud Platform. Amazon Kinesis Data Analytics makes it possible to process data streams in real-time quite easily and fast using Java or SQL. It does not require learning new programming languages or data processing frameworks to accomplish the task.

P.S. Amazon Kinesis Data Firehose captures, transforms, and loads the streams into Amazon Web Services (AWS) data stores. It performs it for real-time analytics with the help of existing Business Intelligence Tools.