grakn - The Knowledge Graph

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The Knowledge Graph





Related Projects

atomspace - The OpenCog hypergraph database, query system and rule engine

  •    C++

The OpenCog AtomSpace is a knowledge representation (KR) database and the associated query/reasoning engine to fetch and manipulate that data, and perform reasoning on it. Data is represented in the form of graphs, and more generally, as hypergraphs; thus the AtomSpace is a kind of graph database, the query engine is a general graph re-writing system, and the rule-engine is a generalized rule-driven inferencing system. The vertices and edges of a graph, known as "Atoms", are used to represent not only "data", but also "procedures"; thus, many graphs are executable programs as well as data structures. The AtomSpace is a platform for building Artificial General Intelligence (AGI) systems. It provides the central knowledge representation component for OpenCog. As such, it is a fairly mature component, on which a lot of other systems are built, and which depend on it for stable, correct operation in a day-to-day production environment.

AmpliGraph - Python library for Representation Learning on Knowledge Graphs https://docs

  •    Python

Open source library based on TensorFlow that predicts links between concepts in a knowledge graph. AmpliGraph is a suite of neural machine learning models for relational Learning, a branch of machine learning that deals with supervised learning on knowledge graphs.

HyperGraphDB - Database for Storing Strongly-Typed Hypergraphs

  •    Java

HyperGraphDB is a general purpose, open-source data storage mechanism based on a powerful knowledge management formalism known as directed hypergraphs. While a persistent memory model designed mostly for Knowledge management, Artificial Intelligence and Semantic web projects, it can also be used as an embedded object-oriented database for Java projects of all sizes. It could also be used as graph database or as (non-SQL) relational database.

agensgraph - AgensGraph, a transactional graph database based on PostgreSQL

  •    C

AgensGraph is a new generation multi-model graph database for the modern complex data environment. AgensGraph is a multi-model database, which supports the relational and graph data model at the same time that enables developers to integrate the legacy relational data model and the flexible graph data model in one database. AgensGraph supports ANSI-SQL and openCypher ( SQL queries and Cypher queries can be integrated into a single query in AgensGraph. AgensGraph is based on the powerful PostgreSQL RDBMS, and is very robust, fully-featured and ready for enterprise use. AgensGraph is optimized for handling complex connected graph data and provides plenty of powerful database features essential to the enterprise database environment including ACID transactions, multi-version concurrency control, stored procedure, triggers, constraints, sophisticated monitoring and a flexible data model (JSON). Moreover, AgensGraph leverages the rich eco-systems of PostgreSQL and can be extended with many outstanding external modules, like PostGIS.

Cayley - An open-source Graph Database

  •    Go

Cayley is an open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. Its goal is to be a part of the developer's toolbox where Linked Data and graph-shaped data (semantic webs, social networks, etc) in general are concerned.

Geist - A personal knowledge base with a focus on connections

  •    Javascript

A personal knowledge base with a focus on connections. The personal knowledge base (PKB) is basically a wiki system for personal use. Unlike a public wiki which most often focuses on representing facts, the PKB can contain subjective material relevant to the person or persons using the PKB. Therefore the desired properties of a PKB are equivalent to those of the personal wiki.

GraphEngine - Microsoft Graph Engine

  •    CSharp

Microsoft Graph Engine is a distributed in-memory data processing engine, underpinned by a strongly-typed in-memory key-value store and a general distributed computation engine.This repository contains the source code of Graph Engine and its graph query language -- Language Integrated Knowledge Query (LIKQ). LIKQ is a versatile graph query language on top of Graph Engine. It combines the capability of fast graph exploration and the flexibility of lambda expression: server-side computations can be expressed in lambda expressions, embedded in LIKQ, and executed on the server side during graph traversal. LIKQ is powering Academic Graph Search API, which is part of Microsoft Cognitive Services.

beam - A distributed knowledge graph store

  •    Go

There's a blog post that's a good introduction to Beam. Beam is a distributed knowledge graph store, sometimes called an RDF store or a triple store. Knowledge graphs are suitable for modeling data that is highly interconnected by many types of relationships, like encyclopedic information about the world. A knowledge graph store enables rich queries on its data, which can be used to power real-time interfaces, to complement machine learning applications, and to make sense of new, unstructured information in the context of the existing knowledge.

GraphView - GraphView is a DLL library that enables users to use SQL Server or Azure SQL Database to efficiently manage graphs

  •    CSharp

GraphView is a DLL library that enables users to use SQL Server or Azure SQL Database to manage graphs. It connects to a SQL database locally or in the cloud, stores graph data in tables and queries graphs through a SQL-extended language. It is not an independent database, but a middleware that accepts graph operations and translates them to T-SQL executed in SQL Server or Azure SQL Database. As such, GraphView can be viewed as a special connector to SQL Server/Azure SQL Database. Developers will experience no differences than the default SQL connector provided by the .NET framework (i.e., SqlConnection), only except that this new connector accepts graph-oriented statements.GraphView is a DLL library through which you manage graph data in SQL Server (version 2008 and onward) and Azure SQL Database (v12 and onward). It provides features a standard graph database is expected to have. In addition, since GraphView relies on SQL databases, it inherits many features in the relational world that are often missing in native graph databases.

Cerebrum : Object-oriented database and knowledge base management system

  •    DotNet

The Object-oriented database and knowledge base management system Cerebrum uses network data model. Cerebrum makes it easier for developers to save the state of the complex objects graph or the neural network into the database.

awesome-network-embedding - A curated list of network embedding techniques.


Also called network representation learning, graph embedding, knowledge embedding, etc. The task is to learn the representations of the vertices from a given network.

Infogrid - Web Graph Database

  •    Java

InfoGrid is a Web Graph Database with a many additional software components that make the development of REST-ful web applications on a graph foundation easy. GraphDatabase is the heart of InfoGrid. Graph database could be replicated across servers. It provides an common interface to store data either in file system or relational or non-relational database.

edgedb - The next generation object-relational database. A @magicstack project.

  •    Python

This is a very early technology preview. It is not yet intended to be used for mission-critical applications. Things may not work, or not work as expected. Comments and bug reports are welcome. EdgeDB is an open-source object-relational database that helps you write better software with less effort. EdgeDB organizes data as a graph of strongly-typed objects and provides an expressive query language which allows to manipulate complex data hierarchies with ease.

g6 - A Graph Visualization Framework in JavaScript

  •    Javascript

G6 is a graph visualization framework. It provides a set of base mechanisms, help developers to build your own graph visualization analysis application or graph visualization edit application.

gunrock - High-Performance Graph Primitives on GPUs

  •    Cuda

Gunrock is a CUDA library for graph-processing designed specifically for the GPU. It uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. For more details, please visit our website, read Why Gunrock, our TOPC 2017 paper Gunrock: GPU Graph Analytics, look at our results, and find more details in our publications. See Release Notes to keep up with the our latest changes.

Infobright - The Database for Analytics

  •    C++

Infobright combines a columnar database with our Knowledge Grid architecture to deliver a self-managing, self-tuning database optimized for analytics. Infobright eliminates the need to create indexes, partition data, or do any manual tuning to achieve fast response for queries and reports.

Gremlin - Graph Traversal Language

  •    Groovy

Gremlin is a graph traversal language. Gremlin works over those graph databases or frameworks that implement the Blueprints property graph data model. It works beter with graph database like TinkerGraph, Neo4j, OrientDB, DEX, Rexster, and Sail RDF Stores. This language has application in the areas of graph query, analysis, and manipulation.

Apache Tinkerpop - A graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP)

  •    Java

Apache TinkerPop is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP). When a data system is TinkerPop-enabled, its users are able to model their domain as a graph and analyze that graph using the Gremlin graph traversal language. Furthermore, all TinkerPop-enabled systems integrate with one another allowing them to easily expand their offerings as well as allowing users to choose the appropriate graph technology for their application.

OpenKE - An Open-Source Package for Knowledge Embedding (KE)

  •    Python

An Open-source Framework for Knowledge Embedding. OpenKE: the main project based on TensorFlow, which provides the optimized and stable framework for knowledge graph embedding models.

Knowledge Discovery Toolbox


KDT provides domain experts with a simple interface to analyze very large graphs quickly and effectively without requiring knowledge of the underlying graph representation or algorithms. It provides a Python interface and can run on clusters.