Welcome to Awesome Graph Universe, a curated list of resources, tools, libraries, and applications for working with graphs and networks. This repository covers everything from Graph Databases and Knowledge Graphs to Graph Analytics, Graph Computing, and beyond.
Graphs and networks are essential in fields like data science, knowledge representation, machine learning, and computational biology. Our goal is to provide a comprehensive resource that helps researchers, developers, and enthusiasts explore and utilize graph-based technologies.
Feel free to contribute by submitting pull requests! 🚀
- Graph Databases
- Graph Engines
- Knowledge Graphs
- Graph Data Science and Analytics
- Graph Computing
- Graph Visualization
- GraphRAG Infrastructure
- Graph Stream Processors
Graph databases are designed to store, manage, and query graph-structured data. They come in two main categories: Property Graphs and Triple Stores. Below are some key tools and their respective languages.
Property graphs allow nodes and edges to have associated properties, making them useful for more detailed graph representations.
- Amazon Neptune
- A managed graph database service that supports both RDF graphs (Triple Store) and property graphs.
- ArangoDB
- Data Graphs
- Ultra-fast graph database SaaS platform, easy to use, with openCypher.
- JanusGraph
- A scalable, distributed property graph database optimized for querying massive graphs.
- KuzuDB
- Memgraph
- Neo4j
- OrientDB
- TigerGraph
Triple stores are designed to store and query RDF (Resource Description Framework) data, which represents information in triples: subject-predicate-object.
- Amazon Neptune
- Blazegraph
- GraphDB
- Stardog
Graph engines are optimized systems for performing queries, computations, and analytics on large graph datasets, leveraging both hardware and software efficiencies.
- AnzoGraph
- Dgraph
- A fast, distributed graph database system designed for real-time query execution.
- GunDB
- A decentralized graph database engine designed for distributed systems.
- KuzuDB
- Memgraph
- PuppyGraph
- TigerGraph
Knowledge graphs connect data points into a rich semantic web of entities and relationships. They are often used in AI applications, search engines, and data integration platforms.
- DBpedia
- A project aimed at extracting structured content from Wikipedia.
- Google Knowledge Graph
- Wikidata
- YAGO
Graph data science focuses on analyzing the structure and patterns in graphs to solve complex problems in domains like recommendation systems, fraud detection, and social network analysis.
- Data Graphs
- GraphTool
- An efficient Python module for manipulation and statistical analysis of graphs.
- GraphX (Apache Spark)
- A component of Apache Spark for graph-parallel computation.
- GraphFrames - GraphFrames is a package for Apache Spark which provides DataFrame-based Graphs in Scala, Java, and Python. Features includes motif finding and a Pregel engine.
- MAGE - Memgraph Advanced Graph Extensions is an open-source graph algorithms library written in C++, Python and Rust.
- Neo4j Graph Data Science
- NetworkX
- TigerGraph Graph Studio
Graph computing refers to the infrastructure and platforms that handle large-scale graph processing, often distributed across multiple machines for speed and scalability.
- Apache Giraph
- GraphFrames (Apache Spark)
- GraphLab
- Pregel
- thatDot Streaming Graph
Graph visualization tools can be used to visualize and interact with graphs, in a way that helps detect patterns in the data. Some are primiraly meant for 
- Gephi
visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free.
- GraphAware Hume
Connected Data Analytics Platform.
- G.V() - A Graph Database Client compatible with Apache TinkerPop enabled graph databases that enables users to write and run Gremlin queries against their database, and visualize the results using various formats (graph visualization, JSON, tables, etc). It's also comes with query debugging/profiling features, and graph data exploration and editing features.
- Kineviz, GraphXR
- Kineviz, GraphXR,Neo4j GraphApp
- Kineviz, SightXR
- Linkurious Enterprise
- Neo4j Bloom
Explore and freely interact with Neo4j’s graph data platform with no coding required.
- NeoDash
- SemSpect
- TheBrain
Organizing notes and documents in a graph structure, with creation of visual representation of relations with the mouse.
- WebVOWL RDF Ontologies visualisation
- yWork, yEd Desktop
Easily draw graphs for illustration, with icons on nodes, styling of labels and relations.
- yWork, yEd Live
- yWorks, Data Explorer for Neo4j
Various 
- Cytoscape
- EasyGraph
- iGraph
- Linkurious, Ogma
- NetworkX
- Orb - Open-source graph visualization library.
- Sigma.js
- yWorks, yFiles for HTML Diagramming SDK to precisely display and interect with different shapes of graphs.
- yWorks, yFiles for Jupyter
GraphRAG refers to using knowledge graphs for the basis of RAG (Retrieval-Augmented Generation) to improve the accuracy of Generative AI responses.
- GraphRAG
- TrustGraph
Graph stream processors enable real-time graph computations within event-stream processing systems. They integrate seamlessly into ETL pipelines or event streams, allowing graph operations to be performed on incoming data streams. These tools consume events, apply graph-based transformations or analyses, and emit processed events, facilitating dynamic graph processing as data flows through the system.
- Quine
Contributions are welcome! If you know of any valuable graph-related resources, tools, or libraries that should be included, feel free to submit a pull request or open an issue.
Please follow the contribution guidelines to maintain the quality and consistency of Awesome Graph Universe.
This repository is licensed under CC0 1.0 Universal, which means you can freely use and contribute to this project.
Happy Graphing! 😊
Inspired by the work of Jean-Baptiste Musso - which is currently inactive.