AWS Kinesis : The Key to Optimizing your Data Processing Pipeline

Recently, we’ve seen companies like Google investing more in tier servers and data centers because of the constant amount of data they receive. That’s what we usually call data streaming, which is an abundance of data coming at once and treated in real time.

AWS Kinesis is one of the many platforms that help companies, or just simple developers, to be able to collect and analyze data in real-time, which allows them to get insights and information quickly. And because of its importance, it will be the subject of my article today.

What is AWS Kinesis and what is it used for?

Based on the official website of Amazon Web Service (AWS), Amazon Kinesis is a tool specially made by them to make the collection, process, and analysis of real-time streaming data easy.

This is a great tool to help companies get insights on the data being collected, to get innovative ideas, and also as a way to prevent any problems.

Now that AWS Kinesis is understood, let’s talk about its multiple uses. The use of it depends on the type of data being processed, could it be videos, audio, application blogs, you name it. There are many companies that rely on this tool for security monitoring and machine learning algorithms.

What are the core services that AWS Kinesis offers?

With what AWS has came out with so far, AWS Kinesis has 4 main core services, that kind of device multiple uses for categories:

  1. 1

    Amazon Kinesis Data Streams: 

    After getting the data as inputs from our devices, this service will ingest and store the data for processing, which will be sent afterward to Amazon Kinesis Data Analytics based on Spark and EC2 among others, and get the insights. 

  2. 2

    Amazon Kinesis Data Firehose: 

    The same as the first one, but for this one, once the data is received, it will be prepared and then loaded continuously to the destination chosen by the user, like Amazon Elasticsearch service, Splunk, Amazon S3, etc.

  3. 3

    Amazon Kinesis Data Analytics: 

    This is the most simple one, as there are no other services in the middle of the process. The data received will go through some SQL queries to be analyzed, and directly get the results.

  4. 4

    Amazon Kinesis Video Streams: 

    This is the most famous one, as the data is received as videos from camera devices, and transferred to Kinesis Video Streams so it can be ingested, stored, encrypted, and indexed for real-time and bash analytics, which is normally for machine learning applications and playback services.

What are the key features of AWS Kinesis that make it stand out?

The key features that make AWS Kinesis stand out from its peers are diverse and depend on which core services you are working with. For example, if we talk about Amazon Kinesis Data Analytics, the following are its main features:

  • Stream Inspection and Visualization

  • Simple Build-and-Run Environment

  • Process using SQL, Python, or Scala

  • Rapid, Serverless Stream Processing Application Development

  • Open Source

  • Integrates with AWS Glue Data Catalog

And I would like to add that Amazon Kinesis Data Analytics includes a large variety of open-source libraries, including Apache Flink, Apache Beam, Apache Zeppelin, AWS SDK, and AWS service integrations, which make it benefit from other features such as

  • Flexible APIs

  • AWS Service Integrations

  • Advanced integration capabilities

  • Compatible with AWS Glue Schema Registry

  • Exactly Once Processing

  • Stateful Processing

  • Durable Application Backups

This is just a glimpse of AWS Kinesis's multiple features, and with each service comes a ton of other interesting features making it the leader in its field.

Case studies of how businesses use AWS Kinesis to improve their operations?

When you want to see the benefits businesses gain from using AWS Kinesis, the example of Gamoshi is the best to bring up.

Gamoshi is a digital advertising and marketing technology company, which needed a tool to upgrade its programmatic advertising model to succeed and reach its role. After some deep research and many tries, the one that gave them the best result was AWS Kinesis.

Based on them, using AWS Kinesis made them:

  • The costs got reduced by 30%

  • The data query time for customers got reduced too

  • Provide a greater range of data queries

  • The regular staffing got reduced by 20%–30%

  • Cleaned, merged, and inserted data in 2–3 seconds

From this great example, we see how using the right tool got this company to get where they are now and benefit a lot from it without wasting a lot of time, effort, and money.

What are the benefits of using AWS Kinesis for data streaming and analysis?

For the benefits, the situation is quite similar to the key features, because it depends on the service used.

For data streaming and analysis in general, these are the main benefits:

  • Works with the streaming data at the same time it's being streamed, and not in batches.

  • It gives real-time insights while the data is being streamed, thanks to it being powered by machine learning.

  • Amazon Kinesis Data Analytics is serverless, which means everything is managed and automated behind the scenes.

  • AWS Kinesis doesn’t need any past knowledge of any languages, frameworks, or machine learning algorithms.

  • And finally, this tool is scalable, which means it automatically adapts your application to the data provided.

What is the pricing and availability of AWS Kinesis?

One of the greatest benefits AW Kinesis has is being a pay-as-you-go service, which makes the user pay only pay for what they used, depending of course on many criteria, such as:

  • The amount of data streamed.

  • The amount of data retrieved and transferred from AWS Kinesis.

  • The number of operations in each stream.

These are just some of the criteria taken into consideration, plus the region you belong to, that might affect the pricing of AWS Kinesis.

For example, the pricing of AWS Kinesis Data Streams in USA Ohio is as

  • Per stream, per hour                                                   $0.04
  • Data ingested, per GB (Includes 24-hour retention)        $0.08
  • Data retrievals, per GB                                                           $0.04
  • Enhanced fan-out data retrievals, per GB                         $0.05
  • Data stored, per GB-month (+24 hours, up to 7 days)    $0.10
  • Data stored, per GB-month (beyond 7 days)                  $0.023

Final Thoughts

With everything being said in this article, AWS Kinesis is a great tool when you are working with a big load of data, and you’re trying to get insight from it and rely on it in your projects.

This tool will help you collect, analyze and get insights from a big amount of data without a lot of effort and especially money.

About the author


Youssef is a Senior Cloud Consultant & Founder of

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