GRAPH DATABASE CHANGES THE AI INDUSTRY

Cheuk Ting Ho

So...
What's a Graph?
And Why?

  • much easier to interpret the model
     

  • understand how it maps to real world entities compared to the relational example

SELECT Name from TABLE where Person_ID = (SELECT mother from TABLE where Name="John")
SELECT Name from TABLE where Person_ID = (SELECT mother from TABLE WHERE Person_ID = (SELECT mother from TABLE where Name="John"))
WOQL.and(
   WOQL.triple("v:Person", "mother", "v:MotherID"),
   WOQL.triple("v:MotherID", "name", "v:MotherName"),
   WOQL.triple("v:MotherID", "mother", "v:GrandmotherID"),
   WOQL.triple("v:GrandmotherID", "name", "v:GrandmotherName"),
)

Storing data semantically (No more data type confussion and cleaning)

???

OWL Graphs

  • by far the most powerful in terms of data modelling capabilities
     
  • 3 simple predicates that enable relationships between object types to be defined:

    rdfs:domain and rdfs:range support strongly typed relationships between objects

    rdfs:subClassOf supports type inheritance

Store data like git - Branch, Merge, Rollback and Collaborate 

  • since the database is also a graph (yup, it is, why not) we can perform git magics
     

  • Git is great for code, but not data
     

  • In the database data are stored in layers for optimum efficiency

  • share and collaborate your data on hub (just like GitHub but for graph data)
     

  • Enable DataOps on Machine Learning
     

  • TerminusHub (comming soon)

 

 

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