Amazon Kinesis

Amazon Kinesis services

Amazon Kinesis is a serverless service that simplifies capturing, processing, and storing real-time data streams at any scale. It allows us to define how we want to process the data streams and integrate the processed data with other AWS services for further analysis. Amazon Kinesis isn’t a single service but rather a suite of services designed to handle real-time streaming data.

There are four primary services under the Amazon Kinesis umbrella:

Amazon Kinesis Data Streams

Amazon Kinesis Data Streams is a fully managed service provided by Amazon Web Services (AWS) that enables us to build real-time applications to process and analyze streaming data at scale.

Let’s look at an example to understand how Kinesis Data Streams work. Here, the stream is produced by web servers called stream producers. This data stream is ingested by Kinesis Data Streams which processes them and sends them to the stream consumers, EC2 instances in this case.

Amazon Data Firehose

Amazon Data Firehose is a service within the Kinesis family specifically designed to deliver real-time data streams to other AWS services for storage, transformation, or further analysis. It acts as a bridge between the processing stage, often handled by Kinesis Data Streams and the destination where we want the data to reside.

Kinesis Data Firehose automates the process of delivering real-time data streams to various AWS services. It eliminates the need to manage complex data transfer processes manually. It takes the processed data streams and delivers them to the designated destinations within the AWS cloud environment. Firehose offers a wide range of delivery options, including popular AWS services like Amazon S3 and Amazon Redshift. It provides basic data transformation capabilities before delivery. We can filter out unwanted data, convert data formats (e.g., CSV to JSON), or perform other data manipulation tasks to ensure the data is optimized for the destination service.

Here, Kinesis Data Firehose picks up processed data packages from Kinesis Data Streams and delivers them to warehouse destination service S3. Consumer applications in EC2 instances then retrieve packages from the warehouses for further processing or analysis.

Amazon Kinesis Video Streams

While Kinesis excels at handling general real-time data streams, Amazon Kinesis Video Streams takes things a step further. It’s a specialized service designed to securely capture, process, and store video streams from various connected devices such as security cameras, drones, body-worn cameras, smartphones, and more.

Kinesis Video Streams offers abilities to analyze videos in real-time. We can ingest footage from surveillance cameras and process them in real-time for fraud detection, anomaly detection, search and rescue operations, and more. It offers a suitable alternative to traditional batch processing.

Amazon Kinesis Data Analytics

Kinesis Data Analytics enables us to process and analyze streaming data using standard SQL. It allows us to create and run powerful SQL code against streaming sources for time series analytics, real-time dashboards, and custom metrics.

How Amazon Kinesis Data Analytics works

To understand the working of Kinesis Data Analytics, let’s divide it into three major components:

• Application: The basic resource in Kinesis Data Analytics is an application. The application is written down in SQL using an interactive editor and tested with live-streaming data.

• Input: An application can continuously read and process streaming data from Amazon Kinesis Data Streams or Amazon Data Firehose. We can enrich the input data by using a reference table, which gets data as objects from the S3 bucket.

• Output: The application executes the SQL queries on the data from the source and stores them in the configured destination, either a Firehose delivery stream or a Kinesis data stream.

The illustration below will help us understand the Amazon Kinesis Data Analytics workflow.

Notice the in-application streams in the illustration above. Kinesis Data Analytics creates these continuously updated streams within the application to perform SQL queries and store intermediate results. We can also partition these streams into multiple in-application streams to improve the throughput.

Benefits of Amazon Kinesis

The benefits Amazon Kinesis offers are discussed as follows:

• Real-time stream processing: Kinesis excels at ingesting and processing data streams as they arrive, enabling us to analyze data in real time rather than waiting for it to be collected and stored entirely. This is crucial for applications that require immediate insights or prompt actions based on the incoming data.

• Scalability: Kinesis can handle data streams of varying sizes. We can easily scale the service up or down based on the processing needs, ensuring it can accommodate fluctuations in data volume.

• Manage multiple streams: Kinesis can simultaneously manage and process data streams from diverse sources. This allows us to consolidate data from different channels into a single platform for unified analysis.

• Integration with other AWS services: Kinesis integrates seamlessly with other AWS services like Amazon S3 for data storage, Amazon DynamoDB for NoSQL databases, and Amazon EMR for big data processing. This integration simplifies the data pipeline and facilitates further analysis of the processed data.