Introduction to GRAph databases

Gabor Dobrei

June 1, 2016

Forrester

• Over 25% of enterprises will be using graph databases by 2017.
• Graph analysis is the true killer app for Big Data.

• Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions after the design of data capture.
• By the end of 2018, 70% of leading organizations will have one or more pilot or PoC efforts underway utilizing graph DBs.

GARTNER

$whoami

Gabor Dobrei

 

twitter/@gabor_dobrei

github/gabordobrei

(meetup/neo4j-budapest-users)

nosql

(NEVER SQL?)

keyvalue
Document
relationaL

 

GRAPH

Volume (~size)

Density

(~complexity)

Volume (~size)

Density

(~complexity)

Key-Value

Volume (~size)

Density

(~complexity)

Key-Value

Column

Volume (~size)

Density

(~complexity)

Key-Value

Column

Document

Volume (~size)

Density

(~complexity)

Key-Value

Column

Document

RDBMS

Volume (~size)

Density

(~complexity)

Key-Value

Column

Document

RDBMS

Graph

Volume (~size)

Density

(~complexity)

Key-Value

Column

Document

RDBMS

Graph

90 % of use cases

GRAPHS ARE EVERYWHeRE

RELATIONSHIPS IN

• Politics
• Economics
• History
• Science
• Transportation
• Social Networks
• Work, Communities

relationships are at least as important as the things they connect

Graphs = Whole > Σ parts

Graph:

Relationships are part of the

data

RDBMS:

Relationships part of the

fixed schema

Q&A

• Complex Questions
• Very expensive global searches/operations
• Constant query time, regardless of data volume

A relational database may tell you the average age of everyone in this session,

but a graph database will tell you who is most likely to buy you a beer

Relational

foo

foo_bar

bar

Relational

foo

foo_bar

bar

Relational

foo

foo_bar

bar

Graph

Graph

Graph

Looks different, who cares?!

• Sample social graph (~ 1000 ppl)
• Avg 50 friends/person
• pathExists(a, b) limited to depth 4
• w/ cache to eliminate disk IO