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sql-queries

Translate and optimize SQL across Snowflake, BigQuery, Databricks, PostgreSQL, and Redshift.

Updated Jan 11, 2026
Search Tags:#optimization#queries#translation#sql#databases#dialects
One-click install
npx skills add https://github.com/chelleboyer/reachy_mini_retail_assistant --skill sql-queries-chelleboyer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sql-queries
Source: https://github.com/chelleboyer/reachy_mini_retail_assistant/tree/main/skills/data/skills/sql-queries
Command: npx skills add https://github.com/chelleboyer/reachy_mini_retail_assistant --skill sql-queries-chelleboyer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Translate and optimize SQL across major dialects to ensure correctness and performance.

Core Features & Use Cases

  • Cross-dialect SQL reference and translation patterns for date/time, strings, arrays, and JSON across Snowflake, BigQuery, Databricks, PostgreSQL, and Redshift.
  • Performance optimization guidance including safe patterns, avoiding common pitfalls like SELECT * and non-partition-filtered scans, plus cost-aware query design.
  • Practical templates for analytics tasks such as building robust window functions, CTEs, rankings, and cohort analyses across engines.
  • Use Case: A data engineer converts a complex PostgreSQL query with multiple CTEs into Snowflake syntax while preserving results and performance.

Quick Start

Convert a PostgreSQL query with window functions to another dialect using the provided templates to see dialect-aware results.

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 from PostgreSQL to Snowflake?▼

SQL query translation from PostgreSQL to Snowflake uses cross-dialect patterns for date/time, strings, arrays, and JSON to preserve window functions and CTEs while ensuring accurate results.

What is the best way to optimize SQL queries for BigQuery and Redshift?▼

SQL optimization for BigQuery and Redshift involves cost-aware query design that avoids SELECT * and non-partition-filtered scans to ensure cost-conscious execution across engines.

Does this approach support cross-dialect window functions and CTEs?▼

Cross-dialect SQL translation supports window functions and CTEs through practical templates for rankings and cohort analyses across Snowflake, BigQuery, Databricks, PostgreSQL, and Redshift.

How do I convert complex PostgreSQL CTEs into Databricks syntax?▼

Converting complex PostgreSQL CTEs into Databricks syntax requires dialect-specific reference templates to map structural differences while maintaining query correctness and performance.

Why should I avoid SELECT * in cross-engine SQL queries?▼

Avoiding SELECT * in cross-engine SQL queries is a performance optimization safeguard because unprojected columns trigger unnecessary data scans, increasing compute costs and degrading execution speed.

When do I need dialect-specific syntax for JSON and ARRAY handling?▼

Dialect-specific syntax for JSON and ARRAY handling is required when translating data analytics workflows across Snowflake, BigQuery, Databricks, PostgreSQL, and Redshift to ensure correct data parsing.

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