Translate a SQL query written for MySQL into Snowflake or BigQuery syntax
Build queries programmatically with the fluent builder API instead of raw SQL strings
Try SQL translation instantly in the browser playground before installing anything
| tobilg/polyglot | justjavac/dvm | grafeodb/grafeo | |
|---|---|---|---|
| Stars | 810 | 705 | 618 |
| Language | Rust | Rust | Rust |
| Setup difficulty | easy | easy | moderate |
| Complexity | 2/5 | 2/5 | 3/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Polyglot is a tool that translates SQL (Structured Query Language, the standard way to talk to databases) from one database dialect to another. Different databases like MySQL, PostgreSQL, Snowflake, and BigQuery all speak slightly different SQL "accents," meaning a query written for one database often won't work on another without changes. Polyglot handles that translation automatically, supporting over 32 dialects. Beyond translation, Polyglot can also parse SQL (break it down into its component parts), format it for readability, and let you build queries programmatically using a fluent builder API, meaning you can construct database queries step by step in code rather than writing raw SQL strings. It's built in Rust, a language known for speed and safety, and ships in multiple forms: as a Rust library, a Python package (installable with pip), and a TypeScript/JavaScript package (installable with npm) that runs in the browser via WebAssembly (Wasm, a way to run compiled code in web browsers). This means you can use Polyglot from almost any programming environment. You would reach for Polyglot when migrating a database from one platform to another, when your app needs to support multiple database backends, or when you want to build tooling that works across different SQL dialects. The playground lets you try it in a browser without installing anything. The full README is longer than what was provided.
A Rust-built tool that translates, parses, and formats SQL queries across more than 32 database dialects.
Mainly Rust. The stack also includes Rust, Python, TypeScript.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.