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sql-queries

Translate SQL queries across Snowflake, BigQuery, Databricks, and PostgreSQL dialects.

Updated Mar 15, 2026
Search Tags:#performance#analytics#sql#query-optimization#databases#dialects
One-click install
npx skills add https://github.com/lilbom32/ketnoitrithuc --skill sql-queries-lilbom32
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sql-queries
Source: https://github.com/lilbom32/ketnoitrithuc/tree/main/.claude/skills/data/1.0.0/skills/sql-queries
Command: npx skills add https://github.com/lilbom32/ketnoitrithuc --skill sql-queries-lilbom32

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Writing SQL that works reliably across multiple data warehouse dialects is error-prone and slows analytics teams. This Skill helps you craft portable, high-quality queries that behave consistently in Snowflake, BigQuery, Databricks, PostgreSQL, and more.

Core Features & Use Cases

  • Cross-dialect SQL generation and translation between major warehouses.
  • Performance-aware query construction using CTEs, window functions, and efficient patterns for large datasets.
  • Use Case: Convert a dialect-specific query into a portable template suitable for multi-dialect analytics pipelines.

Quick Start

Provide a cross-dialect SQL template for a given problem.

Frequently Asked Questions about sql-queries

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I translate SQL queries between Snowflake, BigQuery, and PostgreSQL?▼

To translate SQL queries between Snowflake, BigQuery, and PostgreSQL, you provide the existing query to generate a portable template. This adjusts dialect-specific syntax to function consistently across major data warehouses.

What is the best way to optimize slow SQL queries using CTEs and window functions?▼

The best way to optimize slow SQL queries is applying performance-aware construction using CTEs and window functions. This builds efficient analytical patterns that reduce execution time on large datasets.

Can I build complex analytical queries that work across multiple database dialects?▼

You can build complex analytical queries across multiple database dialects by generating cross-dialect SQL templates. These templates apply dialect-specific syntax and best practices for portability.

Does cross-dialect SQL generation support Databricks and other major warehouses?▼

Cross-dialect SQL generation supports Databricks, Snowflake, BigQuery, PostgreSQL, and other major warehouses. It ensures queries behave consistently by applying dialect-specific syntax rules.

Why does my SQL query fail when moving from PostgreSQL to BigQuery?▼

SQL queries fail moving from PostgreSQL to BigQuery due to dialect-specific syntax differences. Translating queries between dialects adapts functions and structures to match the target warehouse requirements.

How do I write portable SQL templates for multi-dialect analytics pipelines?▼

To write portable SQL templates for multi-dialect analytics pipelines, you input your analytical problem to generate cross-dialect syntax. This applies best practices for portability across target warehouses.

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