28 مستودعات
Declarative systems for defining data structures, validation rules, and expected input types.
Distinguishing note: Focuses on the definition layer of data structures, distinct from the execution or validation logic itself.
Explore 28 awesome GitHub repositories matching data & databases · Data Schema Definitions. Refine with filters or upvote what's useful.
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.
Defines core data structures and field types for the database schema.
Zod is a TypeScript-first schema declaration and validation library designed to ensure end-to-end data integrity. It functions as a runtime type guard, allowing developers to define complex data structures through a declarative, chainable syntax. By using these schema definitions, the library automatically derives static TypeScript types, eliminating the need for manual type duplication and ensuring that runtime data matches expected application contracts. The library distinguishes itself through functional schema composition, which enables the creation of hierarchical structures by nesting a
Define data structures using declarative syntax to specify expected input types and validation rules for reliable type inference throughout an application.
This project is a Python-based framework that functions as a generative AI agent for programmatic data analysis. It enables users to interact with structured data sources through natural language prompts, translating these requests into executable code to perform analysis, data cleaning, and visualization. By maintaining conversational context across multi-turn interactions, the system allows for iterative exploration and the building of complex data narratives. The framework distinguishes itself through a robust semantic layer and secure execution model. It maps raw datasets to descriptive m
Enables annotation of data schemas with types and descriptions to enhance query interpretation.
The Model Context Protocol SDK is a framework for building clients and servers that connect AI models to external data, tools, and resources using a standardized communication protocol. It provides the foundational libraries and interfaces necessary to establish reliable, transport-agnostic connections between AI agents and external systems, enabling seamless information retrieval and task automation. The SDK distinguishes itself through a robust capability negotiation handshake that ensures compatibility between connected parties before exchanging messages. It supports a pluggable transport
Generates standardized data schemas for validating tool inputs and outputs.
Parse Server is a backend-as-a-service solution and Node.js framework that provides a ready-to-use REST and GraphQL API for mobile and web applications. It functions as a core backend infrastructure for managing database schemas, user authentication, and API routing. The system distinguishes itself with a real-time data engine that pushes database updates to clients via WebSockets and a GraphQL server that automatically generates schemas based on application data models. It also features an adapter-based storage layer that abstracts interactions with various cloud and local backends. The pla
Provides tools for creating user-defined schemas and managing database migrations and index retention.
Vitess is a database clustering system for horizontal scaling of MySQL. It functions as a middleware layer that abstracts complex sharding and physical topology, allowing applications to interact with a distributed database environment through a unified interface. By intercepting and routing SQL queries across multiple shards, it enables large-scale data management while maintaining the appearance of a single database instance. The platform distinguishes itself through its ability to perform online schema migrations and distributed transaction coordination without requiring application downti
Maps application-level data structures to physical database shards to help the system understand how to partition and route data effectively.
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
Reuses measures, dimensions, and joins from parent definitions to reduce code duplication.
SQLModel is a type-safe object-relational mapping library for Python that integrates database schema definitions with data validation logic. By combining these two roles into a single class, it allows developers to manage relational data structures and enforce data integrity for web APIs simultaneously. The framework is built to support asynchronous database operations, enabling high-performance applications to execute queries and transactions without blocking the main execution thread. The library distinguishes itself by leveraging Python type hints to provide IDE autocompletion and compile-
Defines data structures that serve as both database schemas and validation models for application logic.
LangChain.js is a framework for building, executing, and monitoring stateful agentic applications. It provides an orchestration engine that models workflows as directed graphs, allowing developers to connect language models, data sources, and external tools into modular, multi-step processes. The platform distinguishes itself through its focus on stateful execution and human-in-the-loop control. It manages agent lifecycles by persisting execution state across threads, enabling fault tolerance and the ability to pause workflows at designated breakpoints for manual review or modification. This
Enforces data consistency for model inputs and outputs using predefined schema types.
Ent is a statically typed entity framework for Go that models database structures as a graph of nodes and edges. It functions as a code generation engine that transforms schema definitions into type-safe database clients, query builders, and migration scripts. By representing data as interconnected entities, the framework enables intuitive traversal of complex relationships and ensures that database interactions remain consistent with the application model at compile time. The framework distinguishes itself through its graph-based approach to data modeling and its reliance on compile-time cod
Uses statically typed objects to define database entities and relationships as the source of truth for code generation.
Awesome GraphQL is a curated directory and resource collection for the GraphQL ecosystem. It serves as a central index for developers to discover libraries, tools, and specifications required for building, testing, and managing data layer implementations across various programming languages. The repository provides access to a comprehensive range of utilities that support the entire GraphQL lifecycle. This includes resources for server-side API development, client-side integration, and schema management. It also highlights tools for security enforcement, such as rate limiting and input valida
Supports schema-first development by providing tools for defining data structures in a language-agnostic format.
Keystone Classic is a Node.js headless content management system and web application framework. It provides a database schema framework for defining structured data models and validation rules to organize information. The system automatically generates a responsive administrative dashboard based on predefined data models and database fields, allowing for content management and record editing without custom administration code. The framework covers identity and security through session state management and password encryption. It includes capabilities for request routing, form submission proc
Provides a declarative system for creating database models using specialized field types for emails, addresses, and relationships.
Convex is a serverless backend platform that provides a real-time reactive database, serverless functions, and state synchronization for web applications. It manages relational JSON documents using ACID-compliant transactions and schema validation to ensure data consistency and integrity. The platform distinguishes itself by synchronizing database state with clients via WebSockets, allowing user interfaces to update automatically as data changes. It also includes a specialized vector search database for performing semantic search using embeddings and supports both cloud-native deployment and
Enforces data integrity and consistent typing across the application through declarative document schemas.
Perspective is a columnar data analytics engine and high-performance visualization component powered by WebAssembly. It provides a system for analyzing and visualizing large or streaming datasets through interactive data grids and charts, utilizing a compiled binary to achieve near-native performance within the browser. The project distinguishes itself through a WebSocket-based data streaming interface and deep Apache Arrow integration, which minimize memory overhead when synchronizing tables between servers and clients. It acts as a remote query proxy capable of translating visualization con
Provides declarative systems for defining columnar data structures and types to hold analysis data.
AI Town is a TypeScript-based simulation engine used to create virtual environments where autonomous characters interact and socialize. It functions as a framework for orchestrating multiple AI agents within a persistent digital world, utilizing language models and a game engine to drive character behavior and social interactions. The project differentiates itself through a dedicated agent sandbox and a vector database agent store, which allow for the management of agent memories and world state. It integrates generative AI for background music and provides tools for simulation world design,
Specifies table structures and field types to ensure data consistency across the simulation store.
Eve is a REST API framework that maps database collections to web resources through declarative configuration files. It functions as a database-to-API mapper, automatically exposing data as RESTful endpoints with built-in support for CRUD operations and schema-based request validation. The project distinguishes itself through a HATEOAS API engine that generates hypermedia links and resource schemas for dynamic client discovery. It also includes an automated Swagger documentation generator that produces interactive specifications for client SDK generation and testing. The framework provides a
Uses declarative systems to define data structures and validation rules for incoming API resources.
CUE is a constraint-based configuration language designed for data validation, schema definition, and code generation. At its core, it unifies types and values into a single concept, enabling compile-time validation that catches structural and value errors before runtime. The language treats data and constraints as the same thing, allowing a single definition to serve as both a schema and concrete configuration data. CUE distinguishes itself through its constraint-based unification engine, which combines multiple configuration sources into a single coherent result by merging their constraints
Defines reusable data schemas using a declarative language for structuring and constraining configuration data.
Vibora هو إطار عمل ويب Python غير متزامن وخادم HTTP مدمج مصمم لبناء تطبيقات ويب عالية الأداء. يستخدم حلقة أحداث غير متزامنة (Event loop) وcoroutines لمعالجة طلبات الشبكة وتقديم الاستجابات دون الحاجة إلى أغلفة خادم خارجية. يتميز المشروع بمدقق مخطط (Schema validator) غير متزامن عالي الأداء لسلامة الطلبات، ومحرك قوالب غير محظور (Non-blocking) مع دعم لإعادة التحميل السريع، وخادم اتصالات WebSocket لتبادل البيانات في الوقت الفعلي ثنائي الاتجاه. يغطي إطار العمل مجموعة واسعة من القدرات، بما في ذلك إدارة المسارات المعيارية عبر المخططات (Blueprints)، وحقن التبعية (Dependency injection) لمكونات التطبيق، وتحليل HTTP بدون نسخ. كما يوفر أدوات لإدارة جلسات المستخدم، وعرض HTML غير متزامن، وعميل HTTP غير محظور مع تجميع الاتصالات. تتوفر واجهة سطر أوامر (CLI) لتهيئة المشروع لإنشاء هياكل دليل موحدة وملفات تكوين أولية.
Allows defining required and optional input fields with default values and custom validation functions.
dlt هي أداة لاستيعاب البيانات بلغة Python وإطار عمل لخط أنابيب ETL مصمم لجلب البيانات من مصادر متنوعة وحفظها في وجهات مهيكلة. تعمل كمحرك لاستنتاج المخطط (schema inference) يكتشف تلقائياً أنواع البيانات ويسطح هياكل JSON المتداخلة في جداول علائقية، ناقلاً البيانات من المصادر إلى بحيرات البيانات، أو المستودعات، أو قواعد بيانات المتجهات. يتميز المشروع بتوليد خط أنابيب مدعوم بالذكاء الاصطناعي، باستخدام نماذج لغات كبيرة لسقالات كود الاستخراج والموصلات لـ REST APIs. كما يدعم تخزين المتجهات متعدد الوسائط والتعبئة المتخصصة لقواعد بيانات المتجهات لدعم تطبيقات الذكاء الاصطناعي والتعلم الآلي. يغطي إطار العمل مجموعة واسعة من القدرات بما في ذلك تطور المخطط المؤتمت، وتحميل البيانات التزايدي عبر تتبع الحالة، والتحقق من جودة البيانات من خلال فرض عقود البيانات. يوفر أدوات لتطبيع البيانات العلائقية، وتحويلات ما قبل وما بعد التحميل، ومجموعة متنوعة من محولات الوجهة لقواعد بيانات SQL ومخازن الكائنات السحابية. تتم إدارة المراقبة من خلال لوحات معلومات تنفيذ خط الأنابيب، وتتبع نسب الأعمدة، والتحقق من إصدار المخطط باستخدام التجزئات القائمة على المحتوى.
Specifies metadata and data types to structure how data is loaded into a destination.
GraphQL-Ruby هو مكتبة Ruby لبناء واجهات برمجة تطبيقات GraphQL بمخطط مكتوب بقوة ومحرك تنفيذ استعلام مخصص. يوفر إطار عمل شاملاً لربط كائنات التطبيق بنظام أنواع رسمي، مما يتيح جلب البيانات المهيكلة من خلال أدوات حل (Resolvers) محددة. يتميز المشروع بآليات متقدمة للأداء والتسليم، بما في ذلك محمل بيانات (Data Loader) للتجميع والتخزين المؤقت لمنع أنماط استعلام N+1. يدعم تسليم البيانات عالي الأداء من خلال بث الاستجابة التزايدي، واستجابات الاستعلام المؤجلة، وجلب البيانات المتوازي باستخدام الألياف (Fibers). بالإضافة إلى ذلك، يوفر دعماً أصلياً لاتفاقيات Relay، بما في ذلك مساعدين متخصصين للاتصالات وتحديد الكائنات. تغطي المكتبة مساحة واسعة من إدارة واجهة برمجة التطبيقات، وتتميز بالتحكم الدقيق في الوصول، وإصدار المخطط للحفاظ على التوافق مع الإصدارات السابقة، والتحديثات في الوقت الفعلي عبر الاشتراكات. كما تتضمن أدوات إدارة حركة المرور لحماية موارد الخادم، مثل تحديد تعقيد الاستعلام وتحديد معدل الطلب. يتم دعم التطوير وقابلية المراقبة من خلال أدوات تحليل AST، وتتبع التنفيذ، وأدوات اختبار متخصصة للتحقق من التحميل المجمع.
Creates structured operations that modify server-side data and return a payload of fields to the client.