5 repositorios
Tools that rewrite SQL constructs between different database dialects, converting vendor-specific syntax into standard equivalents.
Distinct from SQL Dialect Adapters: Distinct from SQL Dialect Adapters: focuses on rewriting existing SQL between dialects rather than providing a unified adapter interface for query execution.
Explore 5 awesome GitHub repositories matching data & databases · Dialect Transformers. Refine with filters or upvote what's useful.
jOOQ is a type-safe SQL query builder for Java that generates code from live database schemas, enabling compile-time validation of SQL syntax and data types. Its core identity is built around a fluent DSL that mirrors SQL structure, a code generator that maps tables, views, and routines to Java objects, and a multi-dialect engine that translates the same DSL into vendor-specific SQL for over 30 databases. The project also includes a SQL parser and transformer for refactoring or dialect conversion, reactive stream integration for non-blocking query execution, and a JDBC proxy diagnostics tool f
Rewrites SQL constructs between dialects, converting vendor-specific syntax into standard equivalents.
Ibis is a portable Python dataframe library and multi-backend query engine that provides a unified interface for executing data transformations across diverse compute engines. It functions as a Python SQL expression compiler and dialect transpiler, allowing users to define data logic once and execute it across cloud warehouses, embedded databases, and distributed clusters without rewriting code. The project distinguishes itself through a database backend abstraction that decouples transformation logic from the underlying execution engine. It enables polyglot data workflows by mixing raw SQL s
Rewrites SQL constructs between different database dialects to ensure cross-backend compatibility.
Querydsl es un framework para la construcción de consultas con seguridad de tipos (type-safe). Utiliza una API fluida y generación de código basada en anotaciones para crear clases espejo a partir de modelos de dominio, permitiendo la validación en tiempo de compilación de consultas de base de datos y eliminando la necesidad de concatenación manual de cadenas. El proyecto proporciona una sintaxis de consulta unificada que se traduce en dialectos específicos para múltiples backends, incluyendo SQL, MongoDB, Lucene y JDO. Admite capacidades de consulta avanzadas como expresiones de tabla comunes, funciones de ventana, operaciones geoespaciales y subconsultas anidadas complejas. Más allá de la recuperación de datos, el framework cubre la ejecución de DML con seguridad de tipos para actualizaciones y eliminaciones masivas, así como el mapeo de resultados en Java Beans, constructores o tuplas. Incluye soporte para consultas de colecciones en memoria y se integra con el Spring Framework para la gestión de transacciones y el manejo de conexiones.
Converts a unified internal query representation into the specific syntax required by different database engines.
MyBatis-Flex is an object-relational mapping framework for Java that extends MyBatis with a fluent API and automated CRUD operations. It provides a data access suite featuring an automatic CRUD data mapper, a type-safe SQL query builder, and a row-based query engine for manipulating records without predefined entity classes. The framework includes a multi-dialect SQL translator that converts generated syntax across different database engines, such as MySQL, PostgreSQL, and Oracle. It further distinguishes itself by offering annotation-free entity mapping using runtime reflection and naming co
Rewrites SQL queries to apply database-specific pagination syntax based on the active dialect.
This project is a relational SQL sample database and synthetic testing dataset. It provides a standardized data model of a fictional digital media store, encompassing business entities such as artists, albums, tracks, customers, and invoices. The dataset is designed as a cross-dialect SQL collection, using compatible scripts to ensure consistent data seeding and environment parity across different database server engines. It combines imported metadata with fictitious personal details to create realistic records for software prototyping and demonstrations. The project covers capabilities for
Populates identical datasets across different SQL server types to maintain environment parity.