Amazon Kinesis is a managed service for collecting, processing and analyzing data streams in real time, and at scale. The service can be used to collect large volumes of data consumed by application processes running on Amazon EC2 instances (a server rental service for running web applications).
Initially launched in 2013 at the Re:Invent conference, it is designed to collect data from thousands of different sources by grouping, aggregating and performing simple manipulations while transferring data from source to destination.
When should Amazon Kinesis be used?
Before going into more detail about how Amazon Kinesis works, let’s take a look at some of the most common use cases:
- Video analysis applications: Secure streaming of video to AWS from connected devices. Examples include connected homes, video surveillance and industrial automation.
- Information gathering on websites, such as user paths, information sharing between different applications, real-time analysis, etc.
- Streaming applications (real-time processing) of various types of information, for fraud detection, very high availability requirements, monitoring of banking flows, etc.
- Processing of data from connected devices (IoT) such as televisions, household appliances, etc.
What are the advantages of Amazon Kinesis?
Amazon Web Services’ real-time data processing service offers great flexibility and adaptability. With this solution, companies can make rapid decisions and adapt their processes accordingly.
Kinesis is scalable and easily adapts to varying workloads and large data volumes, while offering ease of use thanks to its management console. What’s more, it integrates easily with other AWS services, and features enhanced security.
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Focus on architecture
Amazon Kinesis features an architecture based on a large-scale data streaming model, which enables data to be collected, stored and processed in real time from a variety of sources, as shown in the following diagram:
To understand the main elements of its architecture, let’s first look at the data sources used by Amazon Kinesis.
These can come from a wide variety of sources, including web and mobile applications, IoT sensors, enterprise applications and social media.
In general, Amazon Kinesis accepts streaming data from any source capable of sending this type of data.
The main elements of its architecture are as follows:
- Amazon Kinesis Data Streams: Streaming data is stored in Amazon Kinesis Data Streams partitions, which is
- Amazon Kinesis’ high-performance data streaming service.
- Amazon Kinesis Data Firehose: Streaming data is transferred from Amazon Kinesis Data Streams to this service, which can deliver data to various destinations, such as Amazon S3, Amazon Redshift or Amazon Elasticsearch Service.
- Amazon Kinesis Data Analytics: streaming data can be analyzed in real time in this service, using standard SQL language as it arrives.
- Amazon Kinesis Video Streams: This service enables you to capture, store and stream video from a variety of sources, such as IP cameras or smartphones.
Integration with other services
With the aim of creating more complete and efficient data processing solutions, Amazon Kinesis integrates seamlessly with other Amazon services, which we’ll mention here without going into detail:
- The various S3 services, which will store the data collected by Kinesis feeds,
- Amazon EMR, which will enable you to perform more sophisticated real-time analyses on the data collected by Kinesis,
- Amazon Lambda to perform specific processes that can be automatically triggered according to certain events,
Amazon Redshift for access to real-time visualization tools,
- Amazon Elasticsearch to index and search data in real time.
“By integrating Amazon Kinesis with our other services, we’ve created the ideal recipe for businesses to benefit from complete, efficient processing solutions, with enhanced security and reduced costs.”
Amazon Kinesis offers flexible, usage-based pricing. Charges depend on various factors, such as the number of data streams, the number of queries, the volume of data stored and the volume of data transferred.
The basic cost includes an hourly rate for each processing instance, as well as an hourly rate for each replication instance. Additional charges apply, depending on usage and integration with other services.
Amazon Kinesis does, however, offer a free trial period for testing the service, and using the monitoring and cost analysis tools to adjust the fee accordingly.
This article gave us an insight into the power of Amazon Kinesis for real-time data collection, processing and analysis. Thanks to its flexibility and ability to integrate with other AWS services, Kinesis offers businesses a myriad of options. Kinesis’ usage-based costs will vary according to requirements, but optimization tools are available to help companies create solutions to meet specific needs and improve decision-making.
Now that you know all about Amazon Kinesis, you can start training to master the other AWS services. For this, you can choose DataScientest.