Meet Grakn and Graql

Grakn is the knowledge graph, and Graql is the query language.
ER
Grakn allows you to model your domain using the well-known Entity-Relationship model at its full expressivity. It is composed of entity types, relationship types, and attribute types.

Unlike other modelling languages, Grakn allows you to define type hierarchies, hyper-entities, hyper-relations, and rules to build rich knowledge models.
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ER.gql
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# Entity-Relationship

define

person sub entity,
	has name,
	plays employee;

company sub entity,
	has name,
	plays employer;

employment sub relationship,
	relates employee,
	relates employer;

name sub attribute,
	datatype string;

commit 
Grakn and Graql is open source!
Grakn and GraqlGrakn is the knowledge graph engine to organise complex networks of data and making it queryable, by performing knowledge engineering. Rooted in Knowledge Representation and Automated Reasoning, Grakn provides the knowledge foundation for cognitive and intelligent (e.g. AI) systems, by providing an intelligent language for modelling, transactions and analytics. Being a distributed database, Grakn is designed to scale over a network of computers through partitioning and replication.
Hexcomb
grakn bot
SchemaKnowledge SchemaThrough Graql, Grakn provides an enhanced entity-relationship schema to model complex datasets. The schema allows users to model type hierarchies, hyper-entities, hyper-relationships and rules. The schema can be updated and extended at any time in the database lifecycle. Hyper-entities are entities with multiple instances of a given attribute, and hyper-relationships are nested relationships, cardinality-restricted relationships, or relationships between any number of entities. This enables the creation of complex knowledge models that can evolve flexibly.
AnalyticsDistributed AnalyticsGraql natively performs distributed Pregel and MapReduce (BSP) computations on Grakn through its abstraction of OLAP queries. These types of queries usually require custom development of distributed algorithms for every use case. However, Grakn creates an abstraction of these distributed algorithms and incorporates them as part of the language API. This enables large scale computation of BSP algorithms through a declarative language without the need of implementing the algorithms.
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InferenceAutomated ReasoningGrakn’s query language, Graql, performs logical inference through deductive reasoning of data patterns and relationships, in order to derive implicit facts, associations and conclusions in real-time, during runtime of OLTP queries. The inference is performed through entity and relationship type reasoning, as well as rule-based reasoning. This allows the discovery of facts and patterns that would otherwise be too hard to find, the abstraction of complex relationships into its simper conclusion, as well as translation of higher level queries into lower level and more complex data representation.
High LevelHigher-Level LanguageWith the expressivity of the schema, inference through OLTP and distributed algorithms through OLAP, Grakn’s language provides a strong abstraction over low-level data constructs and complex relationships. Graql not only simplifies and reduce lines of code, but it also automatically performs optimisation of query execution. When developers can achieve so much more by writing even less code, productivity rate increases by orders of magnitude.
Grakn KGMS
MEET GRAKN ENTERPRISE KGMS AND WORKBASEThe enterprise knowledge graph management system is designed to scale with the growth of your data and application workload, equipped with all the functionalities you need to deploy and operate in a production environment. Learn More