Aseem Kishore of FiftyThree will be speaking about his experiences building an early-stage startup, The Thingdom, on Neo4j and Node.js: why he and his team chose to build on a graph database, how they did it, and what lessons they learned along the way.

1. BETTING THE COMPANY
(LITERALLY) ON A
GRAPH DATABASE
TIPS, TRICKS, AND LESSONS LEARNED
Aseem Kishore
Jan–Nov 2013

9. START user=node(1), other=node(2)
MATCH (user) -[r1:has|wants]-> (thing) <-[r2:has|wants]- (other)
WHERE TYPE(r1) <> TYPE(r2)
RETURN TYPE(r1), TYPE(r2), thing

11. Daniel Gasienica
@gasi

12. SO…
JUST WHAT IS A
GRAPH DATABASE?

14. # adjacency list:
nodes = List<Node>
neighbors = Map<Node, List<Node>>
neighbors[node1].add(node2)
# adjacency matrix:
nodes = List<Node>
connections = Map<Node, Map<Node, bool>>
connections[node1][node2] = true

19. OKAY...
LET'S TALK ABOUT
WHAT WE LEARNED

20. OUR USAGE
NODE.JS
+
REST API
+
CYPHER

23. WHAT WE LEARNED
Unique, expressive relationship types

27. WHAT WE LEARNED
Unique, expressive relationship types
Cache stats where possible

29. WHAT WE LEARNED
Unique, expressive relationship types
Cache stats where possible
Capture history through event nodes

31. WHAT WE LEARNED
Unique, expressive relationship types
Cache stats where possible
Capture history through event nodes
First-class objects nodes, not rels

34. WHAT WE LEARNED
Unique, expressive relationship types
Cache stats where possible
Capture history through event nodes
First-class objects nodes, not rels
Connected data nodes, not props

36. WHAT WE LEARNED
Unique, expressive relationship types
Cache stats where possible
Capture history through event nodes
First-class objects nodes, not rels
Connected data nodes, not props
Maintain linked lists for O(1) queries

37. NEO4J 2.0+
Labels & constraints
Relationship type grouping
Transactional Cypher
Automatic sharding?

39. AND CHECK OUT...
(MySQL)
—[:TO]—>
(Neo4j)
A DBA PERSPECTIVE
DAVE STERN @ 11:30

40. THANKS!
TWITTER: @ASEEMK
GITHUB: @ASEEMK
EMAIL: ASEEM.KISHORE@GMAIL.COM
Questions?