3 रिपॉजिटरी
Mechanisms for converting complex entities into plain objects or JSON based on configurable field groups.
Distinct from Serial-to-Network Converters: None of the candidates cover the specific ORM pattern of converting entities to JSON with field-level exposure control.
Explore 3 awesome GitHub repositories matching data & databases · Entity Data Serialization. Refine with filters or upvote what's useful.
Mikro-ORM is a TypeScript-based object-relational mapping system that provides a unified persistence layer for Node.js applications. It translates TypeScript entities into relational or document-based database schemas, supporting a variety of engines including PostgreSQL, MySQL, MariaDB, MS SQL Server, SQLite, and MongoDB. The project implements the data mapper pattern to decouple in-memory domain models from the database persistence layer. It utilizes a unit of work pattern to track entity changes in memory and commit them in a single coordinated database transaction. The library covers com
Provides configurable serialization of entity instances into plain objects or JSON formats to control data exposure.
Pony is a Python object-relational mapper that maps classes to relational database tables using an object-oriented interface. It serves as a relational database toolkit providing the means to manage database transactions, identity mapping, and the lazy loading of related records. The project is distinguished by a SQL query translator that converts Python generator expressions into optimized SQL queries by analyzing the abstract syntax tree. It also includes a visual database schema designer for creating entity-relationship diagrams to automatically generate and synchronize relational database
Converts complex relational objects and their associations into dictionaries or JSON strings for API responses.
Ktorm is a lightweight object-relational mapping framework for Kotlin that provides a type-safe SQL domain-specific language and functional sequence APIs for database interaction. It enables developers to define database schemas and map relational tables to interface-based objects, ensuring that data persistence and retrieval are handled through strongly-typed expressions. The framework distinguishes itself by utilizing a functional, collection-style approach to query construction, allowing developers to chain operations like filtering, sorting, and aggregation using idiomatic language patter
Converts entity data into standard formats like JSON or binary streams for storage and transmission.