9 个仓库
Frameworks for mapping application data structures to document-oriented database formats.
Distinguishing note: Specifically targets document-based storage models like MongoDB, distinct from relational ORM mapping.
Explore 9 awesome GitHub repositories matching data & databases · Document Database Modeling. Refine with filters or upvote what's useful.
Mongoose is an object data modeling library and framework for Node.js that maps application objects to MongoDB documents. It functions as a document mapper and schema validator, ensuring consistent data types and validation rules for records stored in MongoDB. The project provides a system for defining structured schemas to model application data, including the ability to create hierarchical data structures through nested schema composition. It implements a middleware-based hook system that allows for the interception and modification of data states during the lifecycle of database operations
Maps application objects to MongoDB documents using structured schemas for data type and validation enforcement.
Vapor is a comprehensive server-side web framework designed for building scalable, high-performance applications and APIs in Swift. It provides a non-blocking, event-loop-based runtime that manages concurrent task processing, background job queues, and asynchronous request handling. The framework is built around a dependency injection container that manages the lifecycle and resolution of services, configurations, and database connections throughout the request pipeline. The framework distinguishes itself through a protocol-oriented design that emphasizes type safety across all layers of the
Model data for document-based storage using custom identifiers, nested structures, and flexible document fields while maintaining the standard database-agnostic interface.
Open-IM-Server is an instant messaging server and cross-platform messaging backend designed for real-time text and media communication. It provides a distributed chat architecture that coordinates user sessions and group communications across multiple server nodes to support millions of concurrent users. The system features a scalable message distribution model that utilizes asynchronous message pipelines and distributed queueing to maintain reliability during traffic spikes. It employs multi-level data caching across local memory and distributed stores to reduce latency and uses a document-b
Employs a document-based data model to store flexible, semi-structured information for diverse message types.
The mongo-go-driver is a Go library for building applications that integrate with a MongoDB document store. It enables the storage and retrieval of flexible document data by providing a bridge between Go backends and the database. The driver implements specialized capabilities for semantic vector search, allowing the handling and execution of high-dimensional vector data for similarity-based retrieval. It also supports full-text search via linguistic analysis and programmatic search index management. The project covers a broad range of database operations, including document-based CRUD, bulk
Supports a flexible document data model to reduce operational complexity and ensure scalability.
This project is a MongoDB database driver and object-relational mapper that brings MongoDB support to the Laravel Eloquent model and query builder. It provides a NoSQL model mapper that allows MongoDB collections to be mapped to object-oriented models using the Active Record pattern. The integration enables the use of a fluent query builder for constructing queries and aggregation pipelines without writing raw database syntax. It supports schema-less model integration, allowing applications to manage unstructured data while maintaining compatibility with standard object-oriented patterns. Th
Maps application data structures to MongoDB documents using the Active Record pattern.
This project is a MongoDB Eloquent ORM and NoSQL query builder for the Laravel framework. It provides an active record implementation that maps MongoDB collections and documents to programmable models for data manipulation. The system enables schemaless data management, allowing applications to handle dynamic data structures without the need for rigid database migrations or predefined tables. It integrates MongoDB into Laravel applications to store and retrieve flexible document data using standard PHP patterns. The library covers document store querying and Eloquent model mapping, utilizing
Maps MongoDB document structures to an object-oriented model system for seamless data manipulation.
本项目是一个全栈 Web 应用程序和服务器端渲染博客的参考实现。它演示了如何使用 Mongoose 对象文档映射器将 Node.js 和 Express 服务器与 MongoDB 数据库集成,以进行基于模式的数据建模。 该应用程序具有完整的用户身份验证系统,支持本地凭据以及通过 OAuth 使用外部身份提供商。它包括会话管理和安全措施,例如加密密码哈希和防止跨站请求伪造 (CSRF)。 该系统涵盖了多种内容管理功能,包括撰写文章和管理社区评论的工作流。它采用服务器端模板渲染来生成动态 HTML 视图,并包含针对云存储和基于环境的凭据管理的配置。 该项目使用 Docker 提供容器化部署模型,以编排 Web 服务器和数据库。
Uses Mongoose to define structured schemas for mapping JavaScript objects to MongoDB documents.
这是一个对象持久化库和数据映射器抽象层。它提供了一组共享接口和基类,旨在将领域逻辑与特定的对象映射器实现解耦,从而将业务领域层与底层数据访问实现分离开来。 该库包含一个数据库模式管理和迁移工具,用于定义、版本化和部署跨不同环境的数据库结构增量更新。它还可用作文档数据库映射器,将对象状态转换为结构化文档格式以进行存储和检索。 该系统涵盖了广泛的持久化功能,包括对象集合的管理以及在不调用构造函数的情况下实例化对象以恢复状态的能力。它还提供了用于数据库模式版本化和调度自定义事件的实用程序,以允许解耦组件对持久化更改做出反应。
Provides a framework for mapping application data structures to document-oriented database formats.
Practicalnode is a comprehensive educational resource and backend development framework for mastering server-side programming with Node.js. It provides a structured approach to building scalable network services, REST APIs, and real-time applications using asynchronous JavaScript. The project serves as a detailed implementation guide for several core backend patterns, including MongoDB data modeling and the construction of REST API development kits. It emphasizes a specific workflow for Docker containerization and offers a variety of strategies for managing user identity through stateless tok
Provides a guide for mapping application objects to schema-based documents in MongoDB.