Leveraging Commercial Graph DB Technologies in Open Source and

Polyglot Application Environments

Brian Clark, VP Product ManagementObjectivity, Inc.

Objectivity, Inc.

• Who we are – Objectivity, Inc.• What we do - InfiniteGraph.• Why InfiniteGraph?• Open Source Polyglot Use Cases.• Other uses of open source in Objectivity, Inc.

Objectivity, Inc.

• The world today is about big data, distributed objects and connections between them.

• Objectivity/DB™ Distributed big data and object management.

• InfiniteGraph™ Connects the dots on a global scale.

Why We’re Different

• Relational databases are not optimized to understand objects or connections.

• Objectivity/DB™ is all about objects and relationships.

• InfiniteGraph™ is all about the connections as first class citizens.

Find Complex Answers Faster with InfiniteGraph’s Distributed Graph

Database• InfiniteGraph is optimized for high speed

traversal of complex relationships.• Return results faster by several orders of

magnitude compared to other technologies.• Performance will not degrade or suddenly

drop-off.

Internal, Confidential

InfiniteGraph in the “NOSQL” Market

InfiniteGraph™

• Connects the dots on a global scale.• InfiniteGraph™ finds connections in big data.

InfiniteGraph Values• Connects the dots on a global scale.

– It’s all about finding, persisting and navigating relationships in big data.

• You can download, develop, deploy at no cost.– InfiniteGraph starts at $0.– You can build for free, and expand as needed.

• Leading the data and graph markets.– No other graph product today can serve the requirements

of enterprise, government and large scale online ventures, as we can.

– InfiniteGraph is the commercial leader in graph technologies for these markets. Our customers are proof.

• Supports large scale and distributed systems.

• Proven technology and deployments.

• Flexible and Easy: • Distributed and cloud ready, Java on interoperable

platforms, integrates with most other data stores, supports ACID to flexible modes.

InfiniteGraph’s Unique Advantages

Relationships are everywhere

Open Source Polyglot Applications

• Where does the graph data come from?• Extracting data from other sources, relational

databases (join tables); key-value stores such as MongoDB; social networks, e.g. Facebook, LinkedIn through public APIs; the Web, e.g. Wikipedia, RDF.

• Using open source to store external keys (e.g. GUID, URI) to InfiniteGraph element ids mapping for very large graphs –billions of nodes and edges.

InfiniteGraph Basic Architecture

Copyright © InfiniteGraph

InfiniteGraph - Core/API

ConfigurationNavigation Execution

Management Extensions

BlueprintsUser Apps

Distributed Object and Relationship Persistence LayerDistributed Object and Relationship Persistence Layer

Session / TX ManagementPlacement

Parallel Ingest

Copyright © InfiniteGraph

InfiniteGraph - Core/API

ConfigurationNavigation Execution

Management Extensions

Session / TX ManagementPlacement

Placement (MDP Plugin)

Distributed Object and Relationship Persistence Layer

App-1(Ingest V1)

App-2(Ingest V2)

App-3(Ingest V3)

App-1(E1 2{ V1V2})

App-2(E23{ V2V3})

App-3

V1V1 V2

V2 V3V3E12

E12 E23E23

Zone 2Zone 1

HostA

Distributed Placement

Copyright © InfiniteGraph

IG Core/API

Distributed Object and Relationship Persistence Layer

ADP Placement

HostB HostC HostX

AddVertex()

Distributed Placement & Pipelining

Copyright © InfiniteGraph

IG Core/API

ConfigurationNavigation Execution

Management Extensions

Session / TX Management

Placement(MDP)

Placement(ADP)

C1C1

C2C2

C3C3

E12E12

E23E23

Targ

et C

onta

iner

s

Pipeline Containers

E(1->2)

E(3->1)

E(2->3)

E(2->1)

E(2->3)E(3->1)

E(1->2)

E(3->2)

E(1->2)

E(2->3)

E(3->1)

E(2->1)

E(2->3)

E(3->1)

E(3->2)

E(1->2)

Pipeline

Agent

Parallel Processing and Storage

Apache HADOOP• Map/reduce

– Distributed processing.

• HDFS– Distributed file system.

• HBase– Distributed storage for large

tables.

• Cassandra– Multi-master database with

no single point of failure.

InfiniteGraph• Distributed processing

– Peer-to-peer servers and clients anywhere in the network.

• Distributed data– Federation of databases

anywhere in the network.

• Single logical view of all data in the federation– Any client anywhere can

access server anywhere.

InfiniteGraph™

• Technical specifications:– Written in: Java (core C++) .– Platforms: Windows (32-bit and 64-bit), Linux (32-

bit and 64-bit), Mac (64-bit).– Graph-Model: Labeled directed multigraph.– API/Protocols: Java, Tinkerpop (which provides

Gremlin, REST, Frames, Ripple and Linked Process).

– Consistency: Flexible (from ACID, to relaxed).– Indexing: Flexible (from automatic to manual)– Persistence: Java class based.

Comprehensive Online Resources

Other uses of Open Source

• Eclipse– IDE for development and samples;– Plug-ins (browsers/visualizer);– SWTBot - UI testing of Visualizer and Assist.

• Apache Ant, Maven, Tycho - build.• Junit – test.• SL4J - plug into log4j and apache logging.• Lucene – text indexing.

Other uses of Open Source

• Xerces C++ – C++ Parser in XML tool suite.• PCRE --> C++ Parser Generator• zlib --> C++ compression• cppcheck - check memory leaks, etc.• ANTLR 3 –Predicate Query Language (parser).• unixODBC – SQL++ access to database.

We’re exhibiting – Booth #708

Brian ClarkVP Product Marketing