Leveraging Commercial Graph DB Technologies in Open Source and Polyglot Application Environments Brian Clark, VP Product Management Objectivity, 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.

InfiniteGraph’s Unique Advantages 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.

Relationships are everywhere CRM, Sales & Marketing Network Mgmt, Telecom Intelligence (Government& Business) Finance Healthcare Research: Genomics Social Networks PLM (Product Lifecycle Mgmt)

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 User Apps Blueprints InfiniteGraph - Core/API Management Extensions Navigation Execution Placement Session / TX Management Configuration Distributed Object and Relationship Persistence Layer Copyright © InfiniteGraph 12

Parallel Ingest App-1 (Ingest V1) App-1 (E1 2{ V1V2}) App-2 InfiniteGraph - Core/API Placement (MDP Plugin) Navigation Execution Management Extensions Placement Session / TX Management Configuration Distributed Object and Relationship Persistence Layer V1 V2 V3 E12 E23 Copyright © InfiniteGraph 13

Distributed Placement AddVertex() IG Core/API ADP Placement Distributed Object and Relationship Persistence Layer Zone 1 Zone 2 HostA HostB HostC HostX Copyright © InfiniteGraph 14

Distributed Placement & Pipelining IG Core/API Management Extensions Navigation Execution Placement (ADP) Placement (MDP) Session / TX Management Configuration Pipeline Agent E(1->2) E(2->3) E12 E(1->2) C1 E(3->1) E(2->1) E(1->2) Target Containers Pipeline Containers E23 E(2->3) E(2->3) E(2->1) C2 E(3->1) E(2->3) E(1->2) E(3->1) E(3->1) C3 E(3->2) E(3->2) Copyright © InfiniteGraph 15

Parallel Processing and Storage Apache HADOOP InfiniteGraph Map/reduce Distributed processing. HDFS Distributed file system. HBase Distributed storage for large tables. Cassandra Multi-master database with no single point of failure. 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 InfiniteGraph.com (main site, content and messaging) Download InfiniteGraph Product Documentation InfiniteGraph Developer Wiki Google Group for Developers Our Blog

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 Clark VP Product Marketing