Graph Model

• Entity-Tables become Nodes
• Foreign Keys become Relationships
• Link Tables become Relationships
• Remove artificial Primary Keys and Foreign Keys

select movie.title
from actors join actor_movie on (...) join movies on (...)
where actors.name = "Andreas"

// find starting points
MATCH (:Person {name:'Andreas'})
// then traverse the relationships
      -[:ACTED_IN]->(movie:Movie)
      <-[:ACTED_IN]-(other:Person)
// and return results
RETURN other

• Cannot model or store data and relationships without complexity
• Performance degrades with number and levels of relationships, and database size
• Query complexity grows with need for JOINs
• Adding new types of data and relationships requires schema redesign, increasing time to market

When data relationships are valuable in real-time traditional database aren't the best choice.

Find all reports and how many people they manage, up to 3 levels down.

MATCH (boss)-[:MANAGES*0..3]->(mgr)

WHERE boss.name = "John Doe"
AND (mgr)-[:MANAGES]->()

RETURN mgr.name as Manager,
       size((mgr)-[:MANAGES*1..3]->()) AS Total

• Model your data naturally as a graph of data and relationships
• Drive graph model from domain and use-cases
• Use relationship information in real-time to transform your business
• Add new relationships on the fly to adapt to your changing requirements

• Relationships are first class citizen
• No need for joins, just follow pre-materialized relationships of nodes
• Query & Data-locality - navigate out from your starting points
• Only load what's needed
• Aggregate and project results as you go
• Optimized disk and memory model for graphs

• Neo4j