Awesome GitHub RepositoriesGraph Data Models

Codegraph is a local codebase indexer and static analysis graph database that serves as a context provider for AI agents. It parses multiple programming languages into a searchable knowledge graph of symbols and dependencies, exposing these relationships to AI tools through the Model Context Protocol. The project distinguishes itself by aggregating relevant code snippets and symbol flows to reduce token usage for large language models. It automates the configuration of server settings and steering instructions across various AI agent platforms and command line editors to enable automatic code

This project is a comprehensive, community-maintained knowledge base and toolkit designed for competitive programming. It serves as a centralized repository for algorithmic theory, data structures, and mathematical techniques, providing a structured reference for informatics and collegiate programming competitions. The project distinguishes itself by integrating educational content with a robust suite of automation utilities. It provides a complete workflow for competitive programming, including tools for automated test case generation, solution verification, and direct interaction with onlin

This project is a project management platform that serves as a centralized digital workspace for organizing team tasks and synchronizing development workflows. It functions as a development workflow orchestrator, providing a unified interface that connects disparate engineering tools to streamline team coordination and maintain visibility over ongoing technical projects. The platform distinguishes itself through a relational entity graph that stores data as a network of interconnected nodes and edges, enabling complex querying of relationships between tasks and repositories. It maintains cons

Graphiti is a backend framework and memory server designed to provide artificial intelligence agents with persistent, time-aware knowledge graph storage. It functions as a memory layer that enables agents to maintain context across long-term interactions by recording and evolving structured data over time. The system distinguishes itself through a specialized temporal graph database that tracks how entities and relationships change using validity windows. By combining semantic vector similarity, keyword matching, and graph topology traversal, the engine performs hybrid retrieval to locate rel

This project serves as a comprehensive technical reference for the architecture and design of data-intensive applications. It provides a structured analysis of the fundamental principles required to build reliable, scalable, and maintainable software systems, covering the core trade-offs inherent in modern data infrastructure. The repository explores the mechanics of distributed data management, including strategies for replication, partitioning, and achieving consensus across multiple nodes. It details the design of storage engines, indexing techniques, and transaction management models, whi

Gun is a decentralized graph database and synchronization engine designed for real-time, peer-to-peer data management. It functions as a JavaScript library that enables applications to maintain consistent state across distributed nodes without relying on a central server. By utilizing conflict-free replicated data types and a gossip protocol, the system ensures that data updates propagate across the network and reconcile automatically. The project distinguishes itself through a focus on decentralized identity and security, utilizing public-key infrastructure to authenticate users and sign dat

SpiderFoot is an open-source reconnaissance and intelligence automation framework designed to streamline the collection and correlation of data for security investigations. It functions as a comprehensive platform that automates the querying of hundreds of public data sources to map digital footprints, identify exposed assets, and uncover potential security threats across an organization's external perimeter. The platform distinguishes itself through a modular, plugin-based architecture that executes data gathering tasks in parallel, supported by a directed graph data model that tracks relati

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

NetworkX is a Python library designed for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. It provides a comprehensive framework for modeling relationships between entities as graphs, directed graphs, or multigraphs, allowing users to attach arbitrary metadata and properties to nodes and edges. The library distinguishes itself through a modular architecture that decouples graph analysis logic from data storage, utilizing nested dictionaries and adjacency lists to manage topology. It features a pluggable backend system that delegates computat

Neo4j is a native graph database management system designed to store and query highly connected data using a property-graph model. It provides an ACID-compliant transaction engine that ensures data integrity, supported by a distributed cluster architecture that maintains causal consistency across nodes. Users interact with the system through a declarative query language, which allows for complex pattern matching and path traversal without requiring manual traversal logic. The platform distinguishes itself through its hybrid approach to data retrieval, combining traditional graph-based queries

Gitdiagram is a software architecture visualization tool that generates interactive diagrams from repository file hierarchies. By performing automated static code analysis, the system maps file structures and component dependencies to provide a visual representation of how different modules relate within a codebase. The platform functions as a searchable documentation catalog, allowing users to discover and explore architectural visualizations of public repositories. It combines server-side rendering for initial delivery with a client-side engine that enables users to dynamically manipulate a

Cayley is a graph database and query engine designed to store and retrieve interconnected data. It functions as a quad store, persisting information as four-element tuples to maintain complex relationships and semantic linked data. The system features a backend-agnostic storage layer that decouples the graph API from the underlying data store. This allows for the integration of external backends through a modular adapter system, enabling the synchronization of data across different storage engines. The project provides a pattern-matching query engine for extracting specific nodes and relatio

Cayley is a graph database engine designed for storing and querying interconnected data using a quad-based data model. It functions as an RDF quad store, managing information through subjects, predicates, objects, and labels. The system features a modular graph store architecture with pluggable backends, allowing it to swap between in-memory storage and various external persistent databases. It includes a GraphQL-inspired API and a dedicated data visualizer for the interactive exploration of nodes and edges. Query capabilities cover bidirectional path traversal and multi-syntax execution usi

DGL is a Python library for building and training graph neural networks. It functions as a graph message passing framework and a geometric deep learning tool, enabling the development of models that analyze graph-structured data. The library is designed for large-scale graph processing, utilizing distributed training and neighbor sampling to handle datasets with billions of edges. It provides specialized support for heterogeneous graph modeling, allowing for the representation of complex real-world entities with multiple node and edge types. Its capabilities cover a wide range of graph tasks

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

Gel is an object-relational database system that models data as a graph of interconnected objects. By utilizing a strongly typed schema, it enables complex relational queries and polymorphic data structures without the need for traditional join tables. The system integrates native vector storage and similarity search operators, allowing it to function as both a relational and a vector database for semantic data retrieval. The platform distinguishes itself through a comprehensive suite of developer-centric automation tools. It features a declarative migration system that tracks and versions sc

Open MCT is a web-based framework designed for visualizing telemetry data and monitoring the health of complex systems. It provides a centralized environment for ingesting, processing, and displaying real-time and historical data streams through customizable operator dashboards. The platform is built on a modular architecture that allows for the integration of external data sources and the addition of custom features through a plugin system. By utilizing a hierarchical object-graph model and a unified interface for time-series data, the framework ensures that information is consistently repre

Ragas is an evaluation framework designed to measure the performance of retrieval-augmented generation pipelines and autonomous agent workflows. It provides a comprehensive suite of tools for benchmarking system outputs, utilizing language models as automated judges to score performance against defined rubrics and reference data. By standardizing inputs, retrieved contexts, and generated responses into a unified schema, the project enables consistent analysis across complex AI applications. The framework distinguishes itself through its ability to generate synthetic test datasets from existin

This project is a collection of programming language references and syntax cheat sheets designed for rapid developer onboarding. It serves as a library of code-based documentation that uses valid source code files to provide whirlwind tours of various language specifications. The project focuses on programming language learning by providing concise, commented code examples that explain core features and syntax in place. This approach enables developers to quickly grasp language-specific patterns, data types, and execution flow through a consistent reference format. The content covers a broad

Nebula is a distributed graph database designed for storing and querying massive volumes of interconnected vertices and edges across a horizontally scalable cluster. It functions as a Kubernetes-native database and a distributed graph analytics engine, utilizing a Raft-based distributed store to ensure strong consistency and high availability. The system features an OpenCypher query engine for performing complex graph traversals and pattern matching. It distinguishes itself with a decoupled compute-storage architecture and a shared-nothing distributed design, allowing query processing and dat