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.

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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

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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

      Solution Architect at Starbust

      Lester Martin

      Educational Engineer at Starburst

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      • Query your data lake fast with Starburst's best-in-class MPP SQL query engine
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