10 dépôts
Data models that combine flexible graph-like links with strict relational storage properties.
Distinct from Graph Data Models: Distinct from Graph Data Models: specifically addresses the hybrid nature of combining relational and graph structures.
Explore 10 awesome GitHub repositories matching data & databases · Graph-Relational Models. Refine with filters or upvote what's useful.
EdgeDB is a graph-relational database that combines a PostgreSQL backend with a graph-based schema and query language. It functions as an object-relational mapper and graph query engine, allowing data to be modeled as objects and links to align storage with modern programming language structures. The system features a composable query language designed to retrieve deeply nested or interconnected data without the use of manual SQL joins. It includes an integrated AI-driven data retrieval solution with built-in support for vector embeddings. The platform provides a schema migration tool for tr
Combines a flexible graph model with relational storage to handle complex datasets and their relationships.
vis is a JavaScript data visualization library used to render interactive networks, timelines, and graphs directly in the web browser. It functions as a relational data mapper and browser-based charting tool, turning complex structured data into dynamic visual patterns to expose entity relationships. The library provides specialized tools for force-directed network graphs, where relational data is represented as interactive nodes and edges. It also includes an interactive timeline component for plotting chronological events and time intervals on a scalable temporal axis. The project covers b
Implements interactive graph visualizations for exploring complex relational connections between entities.
JanusGraph is a distributed, elastically scalable graph database designed to store and query highly connected data across a cluster of machines. It supports the property graph data model with ACID consistency and integrates multi-model search capabilities including geo, numeric range, and full-text queries. The database also includes a Graph OLAP engine for running batch analytics and global graph computations on large datasets using the Hadoop framework. The project distinguishes itself through a masterless cluster architecture that eliminates single points of failure, allowing every node to
A graph database that supports property graph data model with geo, numeric range, and full-text search capabilities.
QOwnNotes is a desktop note editor that stores each note as a plain-text Markdown file on the local filesystem, avoiding proprietary formats and enabling direct file access. It functions as a Nextcloud Notes client, syncing notes and metadata with Nextcloud or ownCloud servers through a companion API service for versioning and sharing. The application also integrates with AI providers and exposes a local MCP server for external agents to search and fetch notes, and includes a companion browser extension for capturing web content, bookmarks, and screenshots. The editor distinguishes itself thr
Displays an interactive visual graph of how notes are linked to each other.
Zotero Style is a plugin for the Zotero reference manager that adds a set of interface enhancements for organizing and exploring research libraries. It provides tools for customizing PDF appearance, adding configurable tag columns with hierarchical nesting, saving and switching between multiple column layout views, tracking reading progress, and visualizing item relationships in an interactive graph. The plugin distinguishes itself through several specific capabilities: a relation graph that displays connected items and supports click-to-locate and focus-node interactions; a reading progress
Provides an interactive graph for visualizing related items with click-to-locate and focus-node interactions.
TypeDB est une base de données orientée graphe fortement typée et un système de gestion de graphes de connaissances. Il sert de magasin de données multi-modèles qui unifie les structures relationnelles, documentaires et de graphes dans un environnement unique, fonctionnant à la fois comme une base de données conforme ACID et un moteur de requête déclaratif. Le système se distingue par l'utilisation de la modélisation par hypergraphes n-aires et de hiérarchies de types polymorphes. Il emploie un schéma fortement typé pour appliquer des règles structurelles et valider l'intégrité des données, permettant une inférence polymorphe basée sur les types et un polymorphisme d'interface basé sur les rôles pour résoudre automatiquement les relations complexes lors de l'exécution des requêtes. La plateforme couvre un large éventail de capacités, notamment le calcul de relations récursives via le tabling, les transactions avec isolation par snapshot et la récupération de données déclarative. Elle prend également en charge la haute disponibilité via la réplication de cluster basée sur le consensus, le contrôle d'accès basé sur les rôles et l'intégration avec des agents IA pour la récupération de données structurées. La gestion est prise en charge via une interface de ligne de commande, et le système fournit des outils pour visualiser les schémas de graphes et auditer l'activité administrative.
Unifies relational, document, and graph structures into a single, strongly-typed multi-model environment.
Apache AGE is a graph database extension for PostgreSQL that adds openCypher graph query capabilities directly within the relational database environment. It functions as a loadable extension that translates Cypher graph traversal queries into SQL expressions, enabling users to run pattern matching and path analysis alongside standard SQL operations within a single database instance. The extension stores labeled, directed property graphs as isolated schemas with internal relational tables for vertices, edges, and labels, preventing cross-graph interference. It supports hybrid query execution
Persists labeled, directed property graphs using relational tables indexed by graph element identifiers.
Kùzu is an embedded property graph database engine designed for high-performance analytical queries and local data management. It operates as a library within the host application process, utilizing a columnar-based storage architecture and just-in-time query compilation to execute complex graph traversals and pattern matching efficiently. By mapping database files directly into system memory, it ensures data durability and high-speed access while maintaining ACID-compliant transactional integrity. The engine distinguishes itself by integrating vector similarity search and full-text search di
Maintains a persistent property graph store to provide context-aware data for retrieval-augmented generation.
This project is a framework for generating synthetic tabular data that preserves the statistical properties and relational integrity of original source datasets. It functions as a metadata-driven engine, utilizing language models to synthesize information even when original training samples are restricted. The system is designed to maintain logical consistency across complex, multi-table structures while ensuring that generated outputs adhere to defined schema requirements. The platform distinguishes itself through a focus on privacy-preserving synthesis, integrating tools to quantify and mit
Maintains logical consistency across multi-table structures by enforcing structural dependencies during data generation.
Simple Graph est un moteur de base de données de graphes léger qui utilise SQLite pour persister les nœuds et les arêtes. Il fonctionne comme un moteur de graphe relationnel en mappant les structures de graphes dans des tables de base de données standard, permettant le stockage à la fois de données structurées et d'informations flexibles sans schéma grâce à l'intégration de documents JSON. Le système fournit un utilitaire pour effectuer des traversées de graphes complexes et la découverte de chemins en tirant parti des expressions de table communes récursives. Cette approche permet l'exploration de connexions profondes et de séquences de nœuds connectés au sein du réseau de données stocké. Le projet prend en charge les opérations de gestion de données standard, y compris la création, la mise à jour et la suppression d'enregistrements de graphes. Toutes les interactions sont gérées par l'exécution d'instructions préparées pour garantir une manipulation cohérente et sécurisée des données au sein du stockage relationnel sous-jacent.
Persists graph structures using JSON objects for nodes and edges within relational tables.