Transforming Data Lakes with Amazon S3 Select & Amazon Glacier Select – AWS Online Tech Talks – #AWS

Data Lakes contain massive amounts of data that companies want to store more cost-effectively and query faster and more efficiently. Amazon S3 Select can increase analytics query performance up to 400%, and Amazon Glacier Select makes it practical to extend queries to archive storage, significantly reducing data lake storage costs. In this webinar, we will demonstrate ways to accelerate analytics applications and extend your data lake to cost-effective archive storage by filtering and retrieving only a subset of data from an S3 or Glacier object instead of retrieving the entire object. We’ll discuss how to use these features with Amazon Athena or Amazon Redshift Spectrum, with third-party software, and we’ll demonstrate a query on an S3-based data lake using a Presto connector.

Learning Objectives:
– Define Amazon S3 Select and Amazon Glacier Select
– Understand the scenarios in which these features can help you increase performance and extend your data lake
– See a before & after scenario of a query with and without Amazon S3 Select

About The Author
- Launched in 2006, Amazon Web Services offers a robust, fully featured technology infrastructure platform in the cloud comprised of a broad set of compute, storage, database, analytics, application, and deployment services from data center locations in the U.S., Australia, Brazil, China, Germany, Ireland, Japan, and Singapore. More than a million customers, including fast-growing startups, large enterprises, and government agencies across 190 countries, rely on AWS services to innovate quickly, lower IT costs and scale applications globally. To learn more about AWS, visit

Tell us what you think...