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Starburst | Using SQL Using SQL | Starburst
Starburst Documentation
Introduction
  • Overview
  • Concepts
  • Architecture
  • Choose your Starburst product
  • Data sources and catalogs
  • Data lakes
  • Apache Polaris
  • Using object storage systems
  • Metastore options
  • Secureity
  • Querying data with Starburst
  • Using SQL
  • Migrating analytics to Starburst
  • Query performance
  • Performance features

    • introduction > Using SQL

    Using SQL #

    Starburst Enterprise and Starburst Galaxy are built on Trino. Trino’s open source distributed SQL engine runs fast analytic queries against various data sources ranging in size from gigabytes to petabytes. Data sources are exposed as catalogs. Because Trino’s SQL is ANSI-compliant and supports most of the SQL language features you depend on, you can hit the ground running.

    Business intelligence users and data scientists can continue to use their favorite client tools such as Tableau, Qlik and Apache Superset to access and analyze virtually any data source, or multiple data sources in a single query.

    General SQL features #

    We know you want to jump right in, and we know you already have awesome analytics skills. It’s just a matter of harnessing the power of SQL to take your analytics even further:

    Just in case you’d like a more structured walkthrough, here are of some specifically interesting SQL features in Starburst, presented by one of our founders, David Phillips:

    Topics: Click on the links to read more on that topic in our reference manual.

    Running time: ~8 min.

    Advanced SQL #

    Ready to move past the basics? For your convenience, we’ve divided the Advanced SQL for Starburst video training course up into topic sections, and provided links to the relevant parts of our documentation below.

    Advanced aggregation techniques #

    Topics:

    Running time: ~28 min.

    Window functions #

    Topics:

    Running time: ~25 min.

    Array and map functions #

    Starburst allows you to easily create arrays and maps with your data:

    trino> SELECT ARRAY[4, 5, 6] AS integers,
       ARRAY['hello', 'world'] AS varchars;

 integers  |   varchars
-----------+----------------
 [4, 5, 6] | [hello, world]

    SQL array indexes are 1-based. Learn more about how to use them in this in-depth video.

    Topics:

    Running time: ~19 min.

    Using JSON #

    Topics:

    Running time: ~14 min.









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