Graph All the Things: An Introduction to Graph Databases

Graph All The Things Introduction to Graph Databases

Neo4j Graph Day 2014 New York

Utpal Bhatt VP Marketing, Neo4j

@bhatt_utpal #neo4j

N e o Te c h n o l o g y, I n c C o n f i d e n t i a l

Creator of Neo4j, the world’s leading graph database.

130 subscription customers, 40+ Global 2000 customers in production.

Open source with 40,000+ downloads per month.

$25M raised to date from Fidelity Growth Partners Europe (London), Sunstone (Copenhagen) and Conor (Helsinki).

NEO TECHNOLOGY CREATORS OF NEO4J

70 people, offices in Munich, Malmö Sweden, London, Paris & San Francisco (HQ).

COMPANY OVERVIEW

“By 2017 more than 25% of enterprises will use graph databases.”


WHEN DO YOU NEED A GRAPH DATABASE?

When your business depends on Relationships in Data


BUSINESS IMPACT OF USING RELATIONSHIPS IN DATA


C34,3%B

38,4%A3,3%

D3,8%

1,8%1,8% 1,8%

1,8%

1,8%

E8,1%

F3,9%

USING RELATIONSHIP INFORMATION IN THE CONSUMER WEB


Use of Relationship Information in The Consumer Web



Use of Relationship Information in The Consumer Web



Unlocking The Business Potential Of Relationships In Data

Graph Databases are purpose built to manage Data and its Relationships

Wide%column,stores,,Data,is,mapped,by,a,row,key,,column,key,and,8me,stamp.,

Key,Value,Stores,,Store,keys,and,associated,values.,

Graph,databases,,Store,data,and,the,rela8onships,between,data.,

Document,stores,,Store,all,data,related,to,a,specific,key,as,a,single,document.,,

DATA,MODEL,RICHNESS,

Adapted from the 451 Group

UNLOCKING THE POTENTIAL OF RELATIONSHIPS IN DATA


The Property Graph ModelTHE PROPERTY GRAPH MODEL


The Property Graph Model

Ann Loves Dan

THE PROPERTY GRAPH MODEL



Ann DanLoves



Ann Dan


(Ann) –[:LOVES]-> (Dan)

Loves



Ann Dan


Loves

(:Person {name:"Ann"}) –[:LOVES]-> (:Person {name:"Dan"})



Ann Dan


Loves




Ann Dan


Loves


Node Relationship Node



Ann Dan


Loves


Node Relationship Node

property propertylabel labeltype



Cypher

Query: Whom does Ann love?

(:Person {name:"Ann"})–[:LOVES]->(whom)

CYPHER


Cypher


MATCH (:Person {name:"Ann"})–[:LOVES]->(whom)

CYPHER


Cypher


MATCH (:Person {name:"Ann"})–[:LOVES]->(whom)

RETURN whom

CYPHER


CypherCYPHER


Under The Hood

MATCH (:Person {name:"Ann"})–[:LOVES]->(whom)RETURN whom

cypher

native graph processing

native storage

UNDER THE HOOD

*“Find all direct reports and how many they manage, up to 3 levels down”

Example HR Query (using SQL)


(SELECT T.directReportees AS directReportees, sum(T.count) AS count FROM ( SELECT manager.pid AS directReportees, 0 AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") UNION SELECT manager.pid AS directReportees, count(manager.directly_manages) AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT manager.pid AS directReportees, count(reportee.directly_manages) AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT manager.pid AS directReportees, count(L2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT T.directReportees AS directReportees, sum(T.count) AS count FROM ( SELECT manager.directly_manages AS directReportees, 0 AS count FROM person_reportee manager WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") UNION SELECT reportee.pid AS directReportees, count(reportee.directly_manages) AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION

(continued from previous page...) SELECT depth1Reportees.pid AS directReportees, count(depth2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT T.directReportees AS directReportees, sum(T.count) AS count FROM( SELECT reportee.directly_manages AS directReportees, 0 AS count FROM person_reportee manager JOIN person_reportee reportee ON manager.directly_manages = reportee.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees UNION SELECT L2Reportees.pid AS directReportees, count(L2Reportees.directly_manages) AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") GROUP BY directReportees ) AS T GROUP BY directReportees) UNION (SELECT L2Reportees.directly_manages AS directReportees, 0 AS count FROM person_reportee manager JOIN person_reportee L1Reportees ON manager.directly_manages = L1Reportees.pid JOIN person_reportee L2Reportees ON L1Reportees.directly_manages = L2Reportees.pid WHERE manager.pid = (SELECT id FROM person WHERE name = "fName lName") ) !

Example HR Query (using SQL)

MATCH (boss)-‐[:MANAGES*0..3]-‐>(sub), (sub)-‐[:MANAGES*1..3]-‐>(report) WHERE boss.name = “John Doe” RETURN sub.name AS Subordinate, count(report) AS Total

Same Query in Cypher


http://m.name/

DATABASE # PEOPLE QUERY TIME (MS)

MySQL 1,000 2,000

Neo4j 1,000 2

Neo4j 1,000,000 2

Neo Technology, Inc Confidential

“Our Neo4j solution is literally

thousands of times faster than the

prior MySQL solution, with queries that require 10-‐100

times less code.”

!-‐ Volker Pacher, Senior Developer eBay

But what about the Real World


UTILIZING RELATIONSHIPS FOR RECOMMENDATIONS

Utilize Relationships in Data to EnableContext-Rich Recommendations

The Solution

David JanePurchased

Order 56

Order 54

Monster energy drink

Low fatfrozen Yogurt

Dairy and eggs

Beverages

Weight Management

Frozen

Order 55

Susan

Customers Orders Product

The NeedClear & Performant Access to Customer, Purchase & Interest Data to make Recommendations

Category


Total DollarAmount

Transaction Count

Investigate

Investigate

UNCOVERING FRAUD RINGS


Utilize Relationship in you Logistics Network work as

a Graph A

B

Utilize Relationship information in your Logistics Network to Minimize Time& Maximize Use of your Network

Utilizing Relationships In Supply Chain And LogisticsMANAGING SUPPLY CHAIN AND LOGISTICS


Utilizing Relationships to diagnose problems and gauge their impact

The SolutionInstantly diagnose problems across 1B+ element networks

The Problem

The Internet Of ThingsPOWERING THE INTERNET OF THINGS


Identity and Access Control

Network Diagnostics

Graph based Search

MORE ENTERPRISE EXAMPLES

Master Data Management

N e o Te c h n o l o g y, I n c C o n f i d e n t i a l Ref: http://www.gartner.com/id=2081316

Interest Graph

Payment Graph

Intent Graph

Mobile Graph

Consumer Web Giants Depends on Five GraphsGartner’s “5 Graphs”

Social Graph

GARTNER’S 5 GRAPHS CONSUMER GIANTS DEPEND UPON 5 THINGS

http://www.gartner.com/id=2081316

Neo Technology, Inc Confidential

!

• Payment Graph (e.g. Fraud Detection, Credit Risk Analysis, Chargebacks...)

• Customer Graph (org drillthru, product recommendations, mobile payments, etc.)

• Entitlement Graph (identity & access management, authorization)

• Asset Graph(portfolio analytics, risk management, market & sentiment analysis, compliance)

• Master Data Graph (enterprise collaboration, corporate hierarchy, data governance)

Finance

Finance

5 GRAPHS OF FINANCIAL SERVICES


GRAPH DATABASES - THE FASTEST GROWING DBMS CATEGORY

Source: http://db-engines.com/en/ranking/graph+dbms!


0%

10%

20%

30%

2011 2014 2017

25%

2.5%

0%

% o

f Ent

erpr

ises

usi

ng G

raph

Dat

abas

es “Forrester estimates that over 25% of enterprises will be using graph databases by 2017”

Sources • Forrester TechRadar™: Enterprise DBMS, Feb 13 2014 (http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801) • Dataversity Mar 31 2014: “Deconstructing NoSQL: Analysis of a 2013 Survey on the Use, Production and Assessment of NoSQL Technologies in the Enterprise” (http://www.dataversity.net) • Neo Technology customer base in 2011 and 2014 • Estimation of other graph vendors’ customer base in 2011 and 2014 based on best available intelligence

“25% of survey respondents said they plan to use Graph databases in the future.”

Graph Databases: Powering The EnterpriseGRAPH DATABASES - POWERING

THE ENTERPRISE

http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801?highlightTerm=&isTurnHighlighting=

http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801

http://www.dataversity.net

N e o Te c h n o l o g y, I n c C o n f i d e n t i a lRef: Gartner, ‘IT Market Clock for Database Management Systems, 2014,’ September 22, 2014

https://www.gartner.com/doc/2852717/it-market-clock-database-management

“Graph analysis is possibly the single most effective

competitive differentiator for organizations pursuing data-

driven operations and decisions after the design of

data capture.”

Graph Databases: Can Transform Your BusinessGRAPH DATABASES - CAN

TRANSFORM YOUR BUSINESS

http://www.gartner.com/id=2081316


Summary

When your business depends on Relationships in Data

SUMMARY

Your Mission: !

!

!

Connect.

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Documents

Graph All the Things: An Introduction to Graph Databases