Join Starburst on May 28th for Launch Point, our new product summit showcasing the future of Starburst.

On-demand webinars

Hadoop modernization on your terms

Your journey to say goodbye to Hadoop should be on your terms, not based on limitations of 'modern' platforms.

In our two-part technical series we dive into engine upgrades, modern hybrid architectures, and building cloud-centric and open data and analytics architecture!

Session 1: Hadoop modernization: AI ready hybrid analytics stack from storage to SQL engine

Session 2: Hive to Iceberg – To migrate, or not to migrate

Scroll for session details.

Fill out the form to access both session recordings. 

Watch on-demand

Sign me up to receive updates and offers from Starburst and its partners. I can opt out at any time.

By clicking Watch now, you agree to Starburst Galaxy's terms of service and privacy policy.

Session 1:Hadoop modernization: AI ready hybrid analytics stack from storage to SQL engine

Your business has decided its finally time to modernize your Hadoop environment! Before you get too far into the weeds, know you have options – you’re no longer forced to go all in the cloud if that’s not what your data, analytics, and AI strategy requires.

In this technical session, we explore best practices to upgrade your on-premises Hadoop architecture with an engine replacement, yes you can simply replace Hive/Impala with enhanced OS Trino, a more price-performant MPP SQL query engine. Feeling more ambitious? Consider building a modern on-premises or hybrid data architecture without Hadoop that is AI ready – with new storage, new compute, access to more data, and faster SQL.

In this session you will learn:

    • How to replace Hive/Impala without touching complicating your HDFS set-up.
    • The benefits of a modern SQL engine that was built to solve the performance challenges of Hive/Impala
    • How to approach a modern on-premises or hybrid architecture that is ready for AI with Starburst + Dell
    • The role an Icehouse, the best version of a data lakehouse can play in your modernization journey

Session 2:Hive to Iceberg – To migrate, or not to migrate

Migrating your Hive tables to Iceberg might seem like a quick fix for turning your data lake into a lakehouse, but it can create more problems than it solves when not done correctly. 

In this workshop, we compare and contrast the architectures of Apache Hive and Apache Iceberg, as well as walk through examples of when migrations would or would not be helpful. The session will conclude with a demo on how Starburst Galaxy can help before, during, and after your migration.

In this session you will learn:

  • The architectural differences between Apache Hive and Apache Iceberg
  • When to consider adopting Apache Iceberg over Apache Hive
  • Best practices to ensure a successful migration
  • How to conduct a migration using Starburst Galaxy

Meet the speakers:

Wei Jiang

Wei Jiang

Solution Architect at Starbust

Lester Martin

Lester Martin

Educational Engineer at Starburst

Cookie Notice

This site uses cookies for performance, analytics, personalization and advertising purposes. For more information about how we use cookies please see our Cookie Policy.

Manage Consent Preferences

Essential/Strictly Necessary Cookies

Required

These cookies are essential in order to enable you to move around the website and use its features, such as accessing secure areas of the website.

Analytical/Performance Cookies

These are analytics cookies that allow us to collect information about how visitors use a website, for instance which pages visitors go to most often, and if they get error messages from web pages.

Functional/Preference Cookies

These cookies allow our website to properly function and in particular will allow you to use its more personal features.

Targeting/Advertising Cookies

These cookies are used by third parties to build a profile of your interests and show you relevant adverts on other sites.