14 repositorios
Tools for defining and structuring data schemas and field hierarchies.
Distinguishing note: No candidates provided; grouping under Data & Databases as it pertains to schema definition.
Explore 14 awesome GitHub repositories matching data & databases · Data Modeling. Refine with filters or upvote what's useful.
Twenty is a headless customer relationship management framework that enables developers to build, version, and deploy custom business applications using code. By utilizing a declarative approach to data modeling, the platform allows for the definition of custom objects, fields, and complex relationships directly within the source code. This schema-driven architecture automatically generates corresponding REST and GraphQL APIs, ensuring that data structures and interface components remain synchronized across development and production environments. The platform distinguishes itself through a m
Connect records from different objects by defining one-to-many or many-to-one relationships, specifying target objects and field names for both sides of the connection.
Payload is a headless content management system and application framework that uses a code-first approach to define data schemas and administrative interfaces. By utilizing a centralized, type-safe configuration object, it automatically generates database schemas, API endpoints, and a fully customizable admin panel. The system is built on a database-agnostic architecture, allowing it to interface with various storage engines while providing a unified, type-safe API for server-side operations, REST, and GraphQL. What distinguishes Payload is its deep extensibility and developer-centric design.
Organizes complex data structures by nesting fields under common properties for improved management.
TypeORM is an object-relational mapper for TypeScript and JavaScript that bridges the gap between object-oriented application code and relational database tables. It provides a comprehensive data persistence layer that allows developers to define database entities using class decorators or configuration objects, enabling seamless interaction with data through object-oriented patterns. The project distinguishes itself through a flexible architecture that supports both the data mapper and repository patterns, alongside a fluent query builder that translates high-level method calls into platform
Implements patterns for structuring and querying tree-like data relationships in relational databases.
SurrealDB is a multi-model database engine designed to store and query document, graph, relational, and vector data within a single ACID-compliant platform. It functions as an AI-native data store, integrating vector search, graph traversal, and machine learning model execution directly into its query layer. By providing a unified declarative query language, the platform eliminates the need for external middleware to synchronize data across different storage models. The platform distinguishes itself through its ability to manage agent memory and complex workflows natively. It allows developer
Represents diverse data structures using native support for arrays, objects, datetimes, and geometry types.
Sequelize is an object-relational mapping library that provides a unified interface for managing relational data through code. By implementing the Active Record pattern, it maps database tables to application objects, allowing developers to perform standard create, read, update, and delete operations using high-level method calls. The library abstracts complex database interactions by translating these calls into optimized, engine-specific SQL statements, ensuring consistent behavior across different database systems. The project distinguishes itself through a comprehensive suite of tools for
Sequelize supports assigning specific database-native types to model columns using built-in options that map directly to database definitions.
Cube is a semantic data layer that provides a unified framework for defining business metrics, dimensions, and relationships across diverse data sources. By acting as a headless business intelligence engine, it transforms raw data into a governed model that can be queried via SQL, REST, and GraphQL interfaces. This architecture ensures consistent data definitions and logic across all downstream analytical applications and reporting tools. The platform distinguishes itself through its integrated conversational AI capabilities, which allow users to explore data using natural language. It orches
Exposes simplified, logical subsets of the underlying data model to downstream consumers.
FoundationDB is an ACID-compliant distributed transactional key-value store. It functions as a scalable database engine that ensures strict serializability and data consistency across a cluster of servers using a shared-nothing architecture. The system is distinguished by its multi-region replication capabilities, allowing data to be synchronized across different datacenters for high availability and disaster recovery. It utilizes optimistic concurrency control to manage distributed transactions and employs a majority-based coordination system to maintain cluster state. The platform provides
Organizes structured data within an ordered key-value store using specific schema and representation techniques.
MobX State Tree is a structured, tree-based state management library for JavaScript applications that combines typed model definitions with reactive snapshots and patch-based change tracking. It provides a reactive state container with runtime and compile-time type safety, where application state is defined as a tree of typed models with collocated actions, computed views, and lifecycle hooks for predictable state mutations. The library is built around an action-centric mutation model that encapsulates all state changes within named functions that directly modify the tree, supported by genera
Checks reference validity and safely handles missing or detached target nodes in the state tree.
Tortoise ORM is an asynchronous object-relational mapper for Python that mirrors Django's model and queryset API while running on asyncio. It defines database tables as Python classes with typed fields and supports foreign key, many-to-many, and one-to-one relations, providing a chainable query API for filtering, annotating, grouping, and prefetching related objects without blocking the event loop. The ORM includes a built-in migration engine that detects model changes, generates migration files, and applies or reverts schema changes through a command-line tool. It connects to PostgreSQL, MyS
Defines database tables as Python classes with typed fields and relationships, mirroring Django's model syntax.
Davinci es una plataforma de inteligencia de negocios y visualización de datos utilizada para construir dashboards e informes interactivos. Funciona como un constructor de dashboards basado en SQL y un servicio de analítica multi-tenant que se conecta a bases de datos mediante JDBC y archivos CSV para transformar datos crudos en componentes visuales. La plataforma se distingue por su modelo de seguridad granular, que incluye permisos a nivel de fila y columna integrados con autenticación LDAP y OAuth2. También proporciona una herramienta de visualización embebida que permite insertar gráficos y dashboards parametrizados y seguros en aplicaciones externas mediante URLs y frames. El sistema cubre una amplia gama de capacidades, incluyendo modelado de datos con plantillas SQL, un motor de diseño drag-and-drop para dashboards responsivos y una amplia variedad de tipos de visualización como diagramas de Sankey, gráficos de radar y mapas geográficos. Incluye además automatización para programar informes por correo electrónico y utiliza caché de clave-valor para optimizar el rendimiento de las consultas.
Enables the definition of data models by categorizing fields as dimensions or metrics for visual rendering.
Codeception es un framework de testing full-stack para aplicaciones PHP que proporciona una interfaz unificada para pruebas unitarias, funcionales y de aceptación. Sirve como herramienta para automatizar navegadores reales de escritorio y móviles mediante el protocolo WebDriver y actúa como cliente para probar APIs REST y SOAP. El framework se distingue por su soporte para Behavior-Driven Development (BDD), permitiendo a los usuarios escribir especificaciones de prueba legibles por humanos en lenguaje Gherkin para alinear las pruebas técnicas con los requisitos de negocio. Implementa un mapeo de acciones basado en actores para conectar estos pasos en lenguaje natural con métodos ejecutables de PHP. Sus capacidades cubren una amplia superficie, incluyendo verificación y gestión del estado de la base de datos para almacenes SQL y NoSQL, la simulación de flujos de trabajo de usuario mediante automatización de navegador y la validación de estructuras de datos de API utilizando JSON y XML. También proporciona herramientas para medir la cobertura de código y gestionar ciclos de vida de pruebas mediante inyección de dependencias y manipulación de contenedores de servicios. El proyecto incluye un proceso de instalación guiado por línea de comandos para generar boilerplates de prueba y archivos de configuración estandarizados.
Interacts with databases via domain models and wraps test actions in roll-backable transactions.
MongoEngine es un mapeador de objetos-documentos (ODM) para Python que traduce registros de base de datos en objetos para proporcionar una interfaz orientada a objetos para la persistencia de datos. Sirve como gestor de documentos y validador de esquemas para MongoDB, mapeando clases a documentos para imponer tipos de datos y reglas de validación. El proyecto proporciona un sistema de queryset de carga perezosa (lazy-loaded) para filtrar, ordenar y agregar colecciones utilizando sintaxis Pythonica. Gestiona estructuras de datos complejas a través de características como la herencia de documentos, el manejo recursivo de documentos incrustados y la vinculación de objetos basada en referencias. La librería cubre amplias capacidades, incluyendo migración de esquemas, búsqueda de texto completo y la gestión de archivos binarios grandes a través del sistema de archivos GridFS. También incluye herramientas para la optimización de índices de base de datos, perfilado del rendimiento de consultas y hooks de ciclo de vida basados en señales para automatizar la lógica durante los eventos de documentos.
Links documents together and defines automatic deletion rules for when a referenced document is removed.
Twill es un kit de herramientas CMS de Laravel y generador de paneles de administración diseñado para construir consolas administrativas personalizadas y sistemas de gestión de contenido. Sirve como un framework de CMS headless y un kit de herramientas para definir modelos de contenido y gestionar datos estructurados a través de una interfaz administrativa dedicada. El proyecto cuenta con un editor de bloques visual que permite a los editores organizar y configurar secciones de contenido reutilizables mediante una interfaz de arrastrar y soltar. Incluye un gestor de activos digitales dedicado para almacenar, recortar y optimizar imágenes y archivos en almacenamiento local o en la nube, así como un gestor de contenido multilingüe para manejar campos traducidos y enlaces permanentes localizados. La plataforma proporciona amplias capacidades para la gestión de contenido y medios, incluyendo seguimiento de versiones, programación de publicaciones y organización jerárquica de páginas. Cubre herramientas administrativas extensas como control de acceso basado en roles, búsqueda global y scaffolding de línea de comandos para la generación rápida de módulos CRUD y migraciones de bases de datos. El sistema se integra con modelos de Laravel utilizando traits para habilitar la publicación y el manejo de medios.
Provides tools for defining and structuring data schemas and field hierarchies for administrative control.
Marksman is a Language Server Protocol implementation for Markdown that provides advanced editor features including autocomplete, go-to-definition, and hover support for markdown files. It serves as an analysis engine to manage documentation and knowledge bases through automated link validation and consistent cross-referencing across multiple documents. The project enables the navigation of complex networks of wiki-style links and headings. It supports content refactoring, allowing users to rename headings and update internal references across multiple files to maintain document integrity dur
Detects broken wiki-links and duplicate or ambiguous headings through real-time diagnostics.