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Welcome to the Starburst Community!

Get connected with the Starburst Community and find all of the support you need to do amazing things with Starburst.

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Starburst Forum

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Trino Champions

Learn about the great work being done with Trino.

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Interact with developers using and building the Trino Open Source Project

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Ready to get started? Our hands-on tutorials walk you through features and scenarios to jump start your learning experience.

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Documentation

Visit our documentation to view information about Starburst Galaxy, Starburst Enterprise, and more.

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Blogs

Why Apache Iceberg will accelerate competition for compute engines

Why Apache Iceberg will accelerate competition for compute engines

Iceberg Partitioning and Performance Optimizations in Trino

Iceberg Partitioning and Performance Optimizations in Trino

Trino for Large-Scale ETL @ Lyft

Trino for Large-Scale ETL @ Lyft

Harnessing Trino for performance engineering and data analytics at Salesforce

Harnessing Trino for performance engineering and data analytics at Salesforce

3 Iceberg partitioning best practices to improve performance

3 Iceberg partitioning best practices to improve performance

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Starburst in the wild

“First lecture was a success! My students ran 1742 SQL queries in 1 hour and Starburst handled it without any issue!” -Zach Wilson

“Hold on to your seats folks, because the Rocketship award for the Data Mesh category is about to blast off! And the winner is none other than Starburst! Congratulations Starburst, you’re a star!” -Modern Data Stack

Five years of hosting the Data Engineering Podcast has provided Tobias Macey with a wealth of insight into the work of building and operating data systems at a variety of scales and for myriad purposes. In order to condense that acquired knowledge into a format that is useful to everyone Scott Hirleman turns the tables in this episode and asks Tobias about the tactical and strategic aspects of his experiences applying those lessons to the work of building a data platform from scratch.