Grakn is a DBMS designed for knowledge bases to intelligent systems. Grakn allows intelligent systems to interpret complex datasets as a single body of knowledge that can be logically reasoned over.


Grakn originally started at the University of Cambridge Computer Lab. It became a commercial product in 2016.

Query Interface

Custom API

Graql is the query language for the Grakn knowledge graph. Graql is declarative. When writing Graql queries, we simply describe what information we would like to retrieve, rather than how should it be obtained. Once we specify the target information to retrieve, the Graql query processor will take care of finding an optimal way to retrieve it. Graql is intuitive. Graql was designed to provide a high-level query language interface with clear and human-readable syntax. By defining high-level application-specific schema, we effectively define our own vocabulary to talk about the domain of interest. By introduction of an explicit data model tightly reflected in the structure of the query language, formulating queries comes naturally as it is reminiscent of building ordinary sentences about our domain. The more tightly the schema represents our domain of interest, the more intuitive writing and reading Graql queries become. Graql serves as both the Data Manipulation Language (DML) as well as the Data Definition Language (DDL) Graql is a language that provides you with a complete set of tools to perform all data-oriented tasks. This includes defining the schema, retrieving information as well as creating and manipulating data.

Data Model

Graph Entity-Relationship

Grakn supports the enhanced entity-relationship model, implemented with a hyper-graph. Users can model type hierarchies, hyper-entities, hyper-relationships, and rules.

Grakn Logo

Source Code

Tech Docs

Former Name



Grakn Labs

Country of Origin


Start Year


Project Type

Commercial, Open Source

Supported languages

Java, JavaScript, Python

Embeds / Uses


Operating Systems

All OS with Java VM, Linux, OS X, Windows