dbt_trino

What problem does it solve?

dbt + Trino projects often fail or underperform due to misconfigured profiles/authentication, incorrect materialization choices, unsafe incremental logic, or missing engine/session/table properties.

Core Features & Use Cases

• profiles.yml setup & authentication: Configure Trino/Starburst connections with the right auth method (none/ldap/kerberos/jwt/certificate/oauth) and production-safe practices like env-var secrets.
• dbt model materializations & patterns: Select the correct materialization (table/view/incremental/materialized_view/ephemeral) and structure a maintainable project (staging → intermediate → marts) that fits Trino/connector capabilities.
• incremental correctness & performance tuning: Implement append/merge/delete+insert strategies, manage on_schema_change behavior, set Iceberg/Hive/Delta table properties, and add session/table properties that reduce scan cost and avoid connector-specific pitfalls.

Quick Start

Use the dbt_trino skill to generate a Trino-targeted profiles.yml and a production-ready incremental model config for Iceberg tables using the merge strategy.