infinite graph nosql meetup dec 2012

Choosing The Right Big Data Tools For The Job – A Polyglot Approach

Leon GuzendaSilicon Valley NoSQL Meetup

December 11, 2012

Current Big Data Analytics

Relationship Analytics

The NoSQL Polyglot Approach

The Big Data Connection Platform

Objectivity Inc.

• Objectivity, Inc. is headquartered in Sunnyvale, CA.

• Objectivity has over two decades of Big Data and NoSQL experience

• We develop NoSQL platforms for managing and discovering relationships and patterns in complex data:

– Objectivity/DB - an object database that manages localized, centralized or distributed databases

– InfiniteGraph - a massively scalable graph database built on Objectivity/DB that enables organizations to find, store and exploit the relationships in their data

Millions of deployments - Our technology is embedded in hundreds of enterprise and government systems and commercial products

Copyright © Objectivity, Inc. 2012

A Typical “Big Data” Analytics Setup

Data Aggregation and Analytics Applications

Commodity Linux Platforms and/or High Performance Computing Clusters

Structured Semi-Structured Unstructured

GraphDB

ObjectDB Doc DB K-V

StoreHadoopColumn

StoreData W/H

RDBMS


Not Only SQL – A group of 4 primary technologies

Simple Highly Interconnected


Relationship Analytics

Incremental Analytics Improvements Aren’t Enough

All current solutions use the same basic architectural model

• None of the current solutions have a way to store connections between entities in different silos

• Most analytic technology focuses on the content of the data nodes, rather than the many kinds of connections between the nodes and the data in those connections

• Why? Because traditional and earlier NoSQL solutions are bad at handling relationships.

• Graph databases can efficiently store, manage and query the many kinds of relationships hidden in the data.


Relationship (Connection) Analytics...A SQL ShortcomingThink about the SQL query for finding all links between the two “blue” rows... it's hard!!

Table_A Table_B Table_C Table_D Table_E Table_F Table_G

There are some kinds of complex relationship handling problems that SQL wasn't designed for.

Relationship (Connection) Analytics...

InfiniteGraph - The solution can be found with a few lines of code

A SQL Shortcoming

A3 G4

Table_A Table_B Table_C Table_D Table_E Table_F Table_G


Applications for Relationship Analytics

LOGISTICS HEALTHCARE INFORMATICS

MARKET ANALYSIS SOCIAL NETWORK ANALYSIS


Representing the Graph...

Combatant A

Civilian Q

Situation Y

Civilian P

Bank X

Civilian S

Civilian R

Events/Places People/Orgs Facts

Situation X

The existing intelligence data might look like this:

Target T

Cafe C S Seen Near TA Banks at X

A Called P

A Seen At Y

A Seen Near X P Emailed S

P Called Q Q Seen Near T

P Called R R Seen Near T

X Paid S

A Eats At


Representing the Graph...

Combatant A

Civilian Q

Situation Y

Civilian P

Civilian S

Civilian R

Events/Places People/Orgs Facts

Situation X

Target T

We start by identifying the nodes (Vertices) and the connections (Edges)

NODES CONNECTIONS

S Seen Near TA Banks at X

A Called P

A Seen At Y

A Seen Near X P Emailed S

P Called Q Q Seen Near T

P Called R R Seen Near T

X Paid SBank X

Cafe C

A Eats At


VERTEX EDGE2 N

...Representing the Graph..

“Nodes” “Connections”


...Representing the Graph..

Situation X Combatant ASeen Near

Civilian P

Called

Called

Seen At Situation Y

Civilian Q

Target T

Seen Near

Emailed

Banks At

Bank X

Civilian S

Seen Near

Called

Civilian R

Seen Near

Paid

Eats At

Cafe C

VERTEX EDGE“Nodes” “Connections”


...Analyzing the Graph...


Civilian P

Called

Called

Seen At Situation Y

Civilian Q

Target T

Seen Near

Emailed

Banks At

Bank X

Civilian S

Seen Near

Called

Civilian R

Seen Near

Paid

Eats At

Cafe C


...Threat Analysis


Civilian P

Called

Called

Seen At Situation Y

Civilian Q

Target T

Seen Near

Emailed

Banks At

Bank X

Civilian S

Seen Near

Called

Civilian R

Seen Near

Paid

SUSPECTS

NEEDS PROTECTION


Graph Databases Can Connect The Dots

DATABASE(S)

GRAPH DATABASE


Visual Analytics


The Polyglot Approach


We (Oracle, Objectivity and Impetus) can help you combine Oracle NoSQL Products with InfiniteGraph to produce...

YOUR BIG DATA CONNECTION PLATFORM

• A high performance distributed database engine that supports analyst-time decision

support and actionable intelligence

• Cost effective link analysis – flexible deployment on commodity resources (hardware

and OS).

• Efficient, scalable, risk averse technology – enterprise proven.

• High Speed parallel ingest to load graph data quickly.

• Parallel, distributed queries

• Flexible plugin architecture

• Complementary technology

• Fast proof of concept – easy to use Graph API.

InfiniteGraph - The Enterprise Graph Database

Copyright © Objectivity, Inc. 2012Copyright © Objectivity, Inc. 2012

InfiniteGraph Capabilities

Parallel Graph Traversal Inclusive or Exclusive Selection

X

X

Shortest or All Paths Between Objects

Start Start

Start Finish Start

Compute Cost To Date

Visualize

Computational & Visualization Plug-Ins


Data Visualization & Analytics

Big Data Connection Platform

*Now HP *Now IBM

Conventional & Relationship Analytics

ORACLE Big Data Solutions

+

Impetus, Oracle and Objectivity can help you combine Oracle NoSQL Products with InfiniteGraph to produce a customized Big Data Analytics Platform


Thank You!

Please take a look at objectivity.comFor InfiniteGraph Online Demos, White Papers,

Free Downloads, Samples & Tutorials

infinite graph nosql meetup dec 2012

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