Broadcast Date: March 20, 2019

Level: 300

In this tech talk, we discuss several options for performing real-time extract, transform, and load (ETL) using Amazon Kinesis, AWS Lambda, AWS Glue, and Amazon S3. We will provide an overview of two different options with distinct advantages for building real-time ETL applications prior to loading a data lake. Our customer, John Deere, will describe how they extract IoT sensor measurements from sophisticated agricultural equipment, transform them into useful customer information in real-time, and load the transformed data into their data lake. They will cover how they use different services for their solution depending on the use case and then dive deep into one example.

Learning Objectives

  • Learn how to decide between what processing to do in real-time and what to do in batch
  • Learn how to perform real-time ETL using Amazon Kinesis Data Firehose, AWS Lambda, and AWS Glue, compared to Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics
  • Learn the pros and cons of the two solutions, and how knowledgeable AWS customers make the decision about how to use one over the other

Who Should Attend?

DevOps, Cloud Architects, Developers


  • Ryan Nienhuis, SPM, Amazon Kinesis Analytics, AWS
  • Gregory Finch, Technology Architect, John Deere

Learn More

To learn more about the services featured in this talk, please visit:

Intro body copy here about 2018 re:Invent launches.

Download the Slide Deck


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