new opportunities for connected data - emil eifrem @ graphconnect boston + chicago 2013

Neo Technology, Inc Confidential

GraphConnect 2013graphs are everywhere

Emil Eifrem@emileifrem

#graphconnect


“Five richest big data sources on the Web include social graph, intent graph,

consumption graph, interest graph and mobile graph.”

http://www.forbes.com/sites/ericsavitz/2012/10/23/gartner-top-10-strategic-technology-trends-for-2013/

- Gartner: “Top 10 Strategic Trends For 2013,” Oct 2012




“[I]t is arguable that graph databases will have a bigger impact on the database landscape than

Hadoop or its competitors.”

- Bloor Research, May 2012

http://www.bloorresearch.com/blog/IM-Blog/2012/5/graph-databases-nosql.html




“Graph analysis is the true killer app for Big Data.”

- Forrester Research, Dec 2011

http://blogs.forrester.com/james_kobielus/11-12-19-the_year_ahead_in_big_data_big_cool_new_stuff_looms_large




http://gigaom.com/2013/05/14/were-witnessing-the-rise-of-the-graph-in-big-data/

GigaOm, May 2013




FastCompany, March 2013http://www.fastcompany.com/magazine/174/exposing-yahoos-strategy-marissa-mayer

http://www.fastcompany.com/magazine/174/exposing-yahoos-strategy-marissa-mayer

http://www.fastcompany.com/magazine/174/exposing-yahoos-strategy-marissa-mayer


Ian Robinson, Jim Webber & Emil Eifrem

Graph Databases

h

Compliments

of Neo Technology


?


NASDAQ:ORCLMarket Cap Today: ~$150B


More recent examples?


Social Graph



Social Graph

Link GraphKnowledge Graph



Social Graph

Interest Graph

Link GraphKnowledge Graph



Connected Data.


Wow.But it looks like graph = social.

Right?


Core Industries & Use Cases:

SoftwareFinancial Services

Telecomm-unications

Network & Data Center Management

MDM

Social

Geo

Early Adopter Segments


Neo4j Adoption Snapshot


SoftwareFinancial Services

Telecomm-unications


MDM

Social

Geo

Select Commercial Customers (Community Users Not Included)



Web / ISVFinance & Insurance

Telecomm-unications


MDM

Social

Geo

Neo4j Adoption SnapshotSelect Commercial Customers (Community Users Not Included)


Neo4j Adoption SnapshotSelect Commercial Customers (Community Users Not Included)

Core Industries & Use Cases: Software

Financial Services

Telecommunications

Web Social, HR & Recruiting

Health Care & Life Sciences

Media & Publishing

Energy, Services, Automotive, Gov’t, Logistics, Education,

Gaming, Other

Network & Data Center

Management

MDM / System of Record

Social

Geo

Identity & Access Mgmt

Content Management

Recommend-ations

BI, CRM, Impact Analysis, Fraud

Detection, Resource Optimization, etc.

Accenture


So what’s this product they’re using?


LIVES WITH

LOVES

OWNSDRIVES

LOVESname: “James”

age: 32twitter: “@spam”

name: “Mary”age: 35

brand: “Volvo”model: “V70”

property type: “car”

Graph data model


Image credits: Tobias Ivarsson

“Whiteboard friendliness”


thobe

Wardrobe Strength

Joe project blog

Hello Joe

Neo4j performance analysis

Modularizing Jython

Image credits: Tobias Ivarsson

“Whiteboard friendliness”


Database # persons query time

MySQL

Neo4j

Neo4j

๏a sample social graph

•with ~1,000 persons

๏average 50 friends per person

๏pathExists(a,b) limited to depth 4

๏caches warmed up to eliminate disk I/O

Graph db performance



MySQL

Neo4j

Neo4j

1,000









MySQL

Neo4j

Neo4j

1,000 2,000 ms









MySQL

Neo4j

Neo4j

1,000 2,000 ms

1,000 2 ms









MySQL

Neo4j

Neo4j

1,000 2,000 ms

1,000 2 ms

1,000,000









MySQL

Neo4j

Neo4j

1,000 2,000 ms

1,000 2 ms

1,000,000 2 ms








Drivers of Graph Adoption

“Why did you use a graph database for your application?”


Drivers of Graph Adoption

Naturally Graphy Data

Complex Graph Queries

Query Performance

0% 20% 40% 60% 80%


Great product.

What’s up next?


Top 12 Month Product Themes



Ease of Use



Big DataEase of Use



Big Data CloudEase of Use


2.0

Q2 Q3 Q4Q12013

Theme: Ease of UseNeo4j 2.0


2.0

• Labels. First expansion of the Property Graph model since its inception. Nodes can have one or more labels. Significantly improve power & ease of use.

Q2 Q3 Q4Q12013



2.0


• Index automation. Improve indexing ease of use, leveraging new “Label” construct Enable indexing operations through Cypher

Q2 Q3 Q4Q12013



2.0



• REST Improvements. Improved Transactionality & Robustness

Q2 Q3 Q4Q12013



2.0



• REST Improvements. Improved Transactionality & Robustness

• Cypher performance improvements.

Q2 Q3 Q4Q12013



Theme: Big Data2.1

Q2 Q3 Q4Q12013

Neo4j 2.1

2014


Theme: Big Data2.1

• Increase upper size limits of single-machine graph

Q2 Q3 Q4Q12013

Neo4j 2.1

2014


Theme: Big Data2.1

• Increase upper size limits of single-machine graph • Performance optimizations targeting densely-

connected nodes

Q2 Q3 Q4Q12013

Neo4j 2.1

2014


Theme: Big Data2.1


connected nodes• Bulk data import improvements: easer & faster to

bring large amounts of data into Neo4j

Q2 Q3 Q4Q12013

Neo4j 2.1

2014


Theme: Big Data2.1


connected nodes• Bulk data import improvements: easer & faster to

bring large amounts of data into Neo4j• Cypher performance improvements

Q2 Q3 Q4Q12013

Neo4j 2.1

2014


GraphConnect BostonJune 10-11, 2013 | Catalyst Restaurantgraphs are everywhere


Your Mission:

Connect.

GraphConnect BostonJune 10-11, 2013 | Catalyst Restaurantgraphs are everywhere