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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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:
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:
Solution Architect at Starbust
Educational Engineer at Starburst