Archive for the ‘InfiniteGraph’ Category

InfiniteGraph 3.3 Release

Tuesday, June 10th, 2014

Achieve Greater Functionality, Ease of Use and Even Faster Performance with InfiniteGraph 3.3

From the post:

Objectivity, Inc., the leader in real-time, complex Big Data solutions, announced today the release of InfiniteGraph 3.3 which offers up improved functionality and ease of use with additional performance improvements.

Objectivity’s products make Big Data smart. Objectivity’s database software helps you discover and unlock the hidden value in your Big Data for improved real-time intelligence and decision support in distributed environments for improved in-time business value.

InfiniteGraph 3.3 performance enhancements include:

  • Faster Data Ingest
  • Significant performance improvements in data ingest operations, as well as in operations that delete vertices and edges.
  • Enhanced Vertex, Edge and Hop Discovery
  • New methods that provide improved functionality for edge, vertex, and hop discovery.
  • Updated Logging
  • Updated SLF4J logging, which includes the ability to customize log output.
  • Updated Tinkerpop Blueprints Implementation
  • Critical Bug Fixes

InfiniteGraph 3.3 is available for a free, unlimited 60 day trial at Get started with our easy Quick Start user guide, Google Group support site and free sample code with vertical use case focus in healthcare, security, social business and more on our InfiniteGraph Wiki site, and resources section,

I keep waiting for a vendor to try the “Avis, we’re #2 so we try harder” strategy with software. 😉

I checked and the InfiniteGraph 3.3 Technical Specifications aren’t posted yet. The 3.2 specs are there but not 3.3. Looking forward to hearing more about improvement for edge, vertex and hop discovery.

Ping me if you see it before I do. Thanks!

Getting Started with InfiniteGraph

Thursday, October 17th, 2013

Getting Started with InfiniteGraph

From the post:

Applications and devices are generating a flood of data that is increasingly dense, highly interconnected and generally unstructured. Social Media is an obvious example where massive amounts of complex data, such as videos, photos and voice recordings are created daily, but there are many other domains where this applies. Markets such as Healthcare, Security, Telecom and Finance are also facing the pain of managing complex, interconnected and real-time information to stay competitive and maintain performance, security, business intelligence and ROI opportunities. .

This type of data of highly-connected entities, some are referring to as the future “Internet of Things”, is not easily managed using a traditional relational databases; emerging technologies and especially graph databases are rising to address these natural graph problems. Using an enterprise-ready, distributed graph database that is complementary to existing architectures, such as InfiniteGraph™, enables organizations to easily store, manage and search the connections and relationships within data and perform rapid analysis in real-time. InfiniteGraph is a distributed, scalable, high-performance graph database that supports developers and companies seeking to identify and utilize the relationships and connections in massive data sets. InfiniteGraph reduces the time needed to discover these connections from days using standard SQL technologies to a matter of seconds.

Given the explosion of data all around us and the increasing need for solutions that can discover and extract value from the relationships within that data, we have developed this comprehensive Software Reviewer’s Guide to help you get started with InfiniteGraph 3.1.

InfiniteGraph 3.1 Software Reviewer’s Guide

This guide takes you step by step from installing InfiniteGraph to navigating your very own graph.

You can download InfiniteGraph 3.1 for free at

The guide is a bit short (sixteen (16) pages) but it should get you started.

I need to install RHEL 4 or 5 64 Bit on a VM before I can try the guide.

I may as well setup a VM for Windows 7 at the same time. So I can copy-n-paste to and from my main system (Ubuntu).

InfiniteGraph 3.1

Tuesday, July 16th, 2013

InfiniteGraph 3.1 Features & Capabilities

From the webpage:

  • Faster Path Finding Provides dramatically improved search results when finding paths between two known objects by leveraging a two-way path finding algorithm.
  • Ingest Enhancements InfiniteGraph 3.1 offers up to 25% improved ingest performance over previous versions.
  • Visualizer Improvements The InfiniteGraph Visualizer provides users with additional ease-of-use and quick start functionality for visualizing and navigating the graph.
  • Storing Graph Views and Navigation Policy Chains Navigation policies, which customize the behavior of a navigation query, and graph views, which define a subset of a graph database for a navigation query, can now be saved in your graph database for later reuse.
  • Unlimited nodes and edges free for 60 days.

When your graph database scales into trillions of nodes, all you need are the facts to get attention.

InfiniteGraph Tutorial: Getting Started With Flight Plan

Sunday, March 31st, 2013

InfiniteGraph Tutorial: Getting Started With Flight Plan

From the post:

Now that you have downloaded Objectivity’s free version of InfiniteGraph, get started with this step by step tutorial using the Flight Plan application to find the fastest and most cost-effective air travel routes available, one of many free applications provided on our InfiniteGraph Developer Wiki site. Download your free version of InfiniteGraph by visiting and follow us on Twitter for the latest updates @InfiniteGraph and get started on building your next generation application today!

The video tutorial illustrates the use of InfiniteGraph but isn’t very accurate in terms of air travel.

I say that because Atlanta was not show as a node on the graph.

“To get to Hell you have to connect through Atlanta.” 😉

A Comparison of 7 Graph Databases

Sunday, January 20th, 2013

A Comparison of 7 Graph Databases by Alex Popescu.

Alex links to a graphic from InfiniteGraph that compares Infinite Graph, Neo4j, AllegroGraph, Titan, FlockDB, Dex and OrientDB.

The graphic is nearly unreadable so Alex embeds and points to a GoogleDoc spreadsheet by Peter Karussell that you will find easier to view.

Thanks Alex and Peter!


Tuesday, October 16th, 2012

Objectivity by Danny Bickson.

Danny has located one of the funniest “connect the dot” videos and a more serious one on InfiniteGraph, a distributed graph database.

Both videos are from Objectivity, maker of InfiniteGraph.

Danny mentions the full version of InfiniteGraph is “…rather expensive.”

Danny must not get out much.

A winning sports team (baseball, football, soccer), a successful business or effective government agency are expensive.

If you want to brag to the server at McDonald’s how cheap your IT costs are, that’s your choice as well.

Sometimes cheapness is its own reward.

How To Use A Graph Database to Integrate And Analyze Relational Exports

Sunday, July 15th, 2012

How To Use A Graph Database to Integrate And Analyze Relational Exports by Todd Stavish.

From the post:

Graph databases can be used to analyze data from disparate datasources. In this use-case, three relational databases have been exported to CSV. Each relational export is ingested into its own sharded sub-graph to increase performance and avoid lock contention when merging the datasets. Unique keys overlap the datasources to provide the mechanism to link the subgraphs produced from parsing the CSV. A REST server is used to send the merged graph to a visualization application for analysis.

Cleaning out my pending posts file when I ran this one.

Would be a good comparison case for my topic maps class.

Although I would have to do in installation work on a public facing server and leave the class members to do the analysis/uploading.

Hmmm, perhaps split the class into teams, some of which using this method, some using more traditional record linkage and some using topic maps, all on the same data.

Suggestions on data sets that would highlight the differences? Or result in few differences at all? (I suspect both to be true, depending upon the data sets.)

Taking a Look at Version 2.1 of Objectivity’s InfiniteGraph

Wednesday, March 21st, 2012

Taking a Look at Version 2.1 of Objectivity’s InfiniteGraph

Paul Williams writes:

InfiniteGraph is a distributed graph database application developed by the California-based company, Objectivity. Companies focused on the relationships within their data make up the primary market for InfiniteGraph. The database is known for its ability to find connections inside large datasets, as well as its robust performance and easy scalability.

InfiniteGraph uses a unique load-based pricing model that allows interested parties to try the software, including full database development, essentially free of charge. Two pricing options exist for companies deciding to fully deploy InfiniteGraph. The first option is “pay as you go,” which sports a run-time usage-based pricing model. Companies with large or classified applications can take advantage of a site-wide license option.

Those interested in using the free demo version of InfiniteGraph need to either have a Java compiler combined with some skill using a command line, or an installed IDE such as Eclipse. Database model development in InfiniteGraph requires at least some basic familiarity with the Java language, considering models and relationships (vertices and edges in InfiniteGraph nomenclature) are defined as Java classes. Once a database is compiled, the InfiniteGraph Visualizer app (included with package) allows for graph navigation and data browsing.

Objectivity might benefit from providing a pre-compiled database with the InfiniteGraph download package, so interested parties can investigate the Visualizer app and the software’s data mining capabilities without the need of a Java compiler and/or having to engage their development staff.

Just going off of the review for the moment, I think having a common navigation of data and metadata is a good thing. That is offset by the rather unnatural load a graph database and search for a node before there is a display.

I think I understand the reasoning for the search for a node first before displaying but it is counter-intuitive, where counter-intuitive = burden on user. Better to provide for (and use) a default node that is displayed upon load. That way “load” produces some action the user can see. And offer the user the ability to pick another “default” node that loads automatically when the graph is loaded.

It sounds like the documentation could be better integrated into the application (and not left on the vendor’s website).

Comments or suggestions on strong/weak points to look for with InfiniteGraph?

Everything Goes Better With Bacon

Wednesday, February 29th, 2012

Everything Goes Better With Bacon by by Nick Quinn, Senior Software Developer, InfiniteGraph.

From the post:

Whenever someone considers a large movie database like Internet Movie Database, or IMDB, inevitably the classic six degrees of Kevin Bacon problem comes up. It is a famous problem posed like this, “…any individual involved in the Hollywood, California film industry can be linked through his or her film roles to actor Kevin Bacon within six steps” []. This problem even helped Kevin Bacon begin his own social charity organization called linking people with charities that they might be interested in.

Below is an example of how InfiniteGraph can be used to store and navigate through large sets of connected data like the IMDB. In the example, I will show how to both find the links between various actors and Kevin Bacon, but also how to output the navigation results in various formats including JSON and GraphML. Note: Custom navigator plugins and custom formatter plugins (including the default JSON/GraphML formatters) can be created and used in any InfiniteGraph (2.1) graph database instance. See the InfiniteGraph developer wiki for more details and examples of how to write and use custom plugins (

Here is a visualization of the actors connected to Kevin Bacon within just two degrees of separation (up to 1500 connections).

Even if you are not interested in movies or Kevin Bacon (there are a few of us around), this post rocks!

Good demonstration of the power of a graph database (in this case, InfiniteGraph) for navigation of relationships in data.

Code for visualization as well!

InfiniteGraph – “…Create, Define, Repeat, and Visualize Results in Minutes”

Tuesday, February 21st, 2012

Objectivity Adds New Plugin Framework, Integrated Visualizer And Support For Tinkerpop Blueprints To InfiniteGraph

From the post:

“Of the numerous varieties of NoSQL databases, graph databases have the potential to significantly alter the analytics sector by enabling companies to unlock value based on understanding and analyzing the relationships between data,” said Matt Aslett, research management, data management and analytics, 451 Research. ”The new additions to Objectivity’s InfiniteGraph enable developers to achieve results in real time and also realize additional value by making the queries repeatable.”

Plugin Framework:
InfiniteGraph’s Plugin Framework provides developers with the ultimate in flexibility and supports the creation, import, and repeated use of plugins that modularize useful functionality. Developers can leverage successful queries, adjust parameters when appropriate, test queries and gain real-time results. A Navigator plugin bundles components that assist in navigation queries, e.g. result qualifiers, path qualifiers, and guides. The Formatter plugin formats and outputs results of graph queries. These plugins can be loaded and used in the InfiniteGraph Visualizer, and reused in InfiniteGraph applications.

Enhanced IG Visualizer:
The Visualizer is now tightly integrated with InfiniteGraph’s Plugin Framework allowing indexing queries for edges and export of GraphML and JSON (built-in) or other user-defined plugin formats. The Visualizer allows users to easily load plugins with enhanced control and navigation. Developers can parameterize plugins to control runtime behavior. Now every part of the graph is fully customizable and delivers a sophisticated result display for each query.

Support for Tinkerpop Blueprints:
InfiniteGraph provides a clean integration with Tinkerpop Blueprints, a popular property graph model interface with provided implementations, and is well-suited for applications that want to traverse and query graph databases using Gremlin.

That’s a bundle of news at one time for sure! The plugin architecture sounds particularly interesting.

Curious if anyone has developed a JDBC that enables access to data in a relational database as a graph?

Infinitegraph 2.0

Friday, December 2nd, 2011

Infinitegraph 2.0

From the product page:

InfiniteGraph helps organizations find the valuable relationships within their data. Our product is unique in its ability to leverage distributed data and processes, which yields reduced time and costs while maximizing overall performance on big data.

No other graph database technology available today can match InfiniteGraph’s combined strengths of persisting and traversing complex relationships requiring multiple hops, across vast and distributed data stores.

But here is more important information (Objectivity, Inc. is the owner of Infinitegraph 2.0):

Objectivity, Inc., the leader in distributed, scalable data management solutions, today announced that Government Security News (GSN) has named its flagship database, Objectivity/DB, as winner of its annual Homeland Security Awards program in the “Best Intelligence Data Fusion and Collaborative Analysis Solution” category. The annual GSN Homeland Security Awards program celebrates the ongoing public-private partnership between all branches of Federal, state and local government in the United States and the private sector vendors of IT security, whose combined efforts successfully defend and protect the nation’s people, property and way of life. Click here for a list of awards categories and finalists, as well as for more information on GSN’s Homeland Security Awards.

“GSN is an authoritative source of news and information on all aspects of homeland security, and we are honored to be recognized by their esteemed panel of judges,” said Jay Jarrell, president and CEO of Objectivity, Inc. “This award is a testament to our leadership in the government sector, and underscores how agencies like the U.S. Air Force’s Network Centric Collaborative Targeting System (NCCT), Analyst Support Architecture (ASA) and the U.S. Navy’s Broad Area Maritime Surveillance (BAMS) Unmanned Aircraft System (UAS) program are leveraging Objectivity/DB to power distributed mission critical intelligence data fusion and collaborative analysis.”

Note that I corrected the first link in the first paragraph to point to the news of the award dinner. BTW, Netwitness and Overwatch Textron Systems were also winners in the “Best Intelligence Data Fusion and Collaborative Analysis Solution” category. Both worth your attention as well.

In terms of seeking an audience to discuss homeland security solutions, I think basing your approach on award winning software would be a good idea.

InfiniteGraph and RDF tuples

Thursday, September 8th, 2011

InfiniteGraph and RDF tuples

Short answer to the question: “[Does] InfiniteGraph supports RDF (Resource Descriptive Framework) tuples (triples), whether it works like a triplestore, and/or if we can easily work alongside a triple store[?]”


It also raises the question: Why would you want to?

Developer Contest: Win Apple Stuff!

Thursday, August 25th, 2011

Developer Contest: Win Apple Stuff!

From the website:

Build a cool software application, web or mobile service around social, game and/or location-based networks, using InfiniteGraph to traverse the objects and relationships in your data. You could win up to $12,000 worth of Apple products, gear and tech!

Presentation and code due 30 September 2011.

What objects and relationships are in your data?

InfiniteGraph Steps Out of Beta…

Thursday, August 25th, 2011

InfiniteGraph Steps Out Of Beta To Help Companies Identify Deep Relationships In Large Data Sets

From the article:

Working with these kind of large enterprises requires support for billions of data points, and so InfiniteGraph has built a system to enable scaling and big data capacity, with realtime functionality. Today, InfiniteGraph is expanding its reach to businesses and developers looking to mine their data stores for complex relationships, be they enterprise apps targeting SMBs, SMEs themselves, or Fortune 500 companies.

But the important thing to point out about InfiniteGraph’s commercial release (the system has been being developed in beta over the last year) is that it doesn’t require developers to re-engineer their databases from scratch to benefit from the technology. Developers can simply use the platform’s dedicated graph API to leverage InfiniteGraph’s relationshop mining on top of their existing data. It also offers a high-scale database management system, which is a nice bonus.

Other features of note in InfiniteGraph’s commercial release include parallel data loading and accelerated ingest, meaning that developers can import and continuously feed apps with data from multiple input streams more speedily. The graph database also allows developers to choose from different indexing options that suit their company’s specific needs (from automatic to manual), as well as enabling devs to view, verify, and test data models in customizable approaches. (emphasis added)

Sounds like topic map navigation of information doesn’t it?

Check it out:

Connecting the dots in big data (Tuesday 16 August 2011)

Saturday, August 13th, 2011

Connecting the dots in big data

From the post:

Join us Tuesday August 16, 2011 (11:00am PT / 2:00pm ET), for a webinar with InfiniteGraph and DBTA (Database Trends and Applications), where we’ll be giving an introduction to InfiniteGraph, and speaking about connecting the dots to find meaning in big data.

Big Data problems are quickly presenting themselves in almost every area of computing from Social Network Analysis to File Processing. Many technologies, such as those in the NoSQL space were developed in response to the limitations of current storage systems as an effective mechanism to deal with these mountains of data. And much of that data is interconnected in ways that, when organized properly, gives interesting and often valuable information.

InfiniteGraph, the distributed and scalable graph database, was designed specifically to traverse connections and provide the framework for a new set of products built to provide real-time business decision support and relationship analytics. This presentation examines the technology behind InfiniteGraph and explores a couple of common use cases involving very large scale graph processing.

Objectivity Infinite Graph (timed associations?)

Monday, May 9th, 2011

Objectivity Infinite Graph

Curt Monash that reports his conversation with Darren Wood, the lead developer for the Infinite Graph database product.

From last June (2010) but I think after reading it, you will agree it was worth bringing up.

A couple of goodies from his thoughts on edges:

  • Edges are first-class citizens in Infinite Graph, just as nodes are.
  • In Infinite Graph, edges can also have effectiveness date intervals. E.g., if you live at an address for a certain period, that’s when the edge connecting you to it is valid.

The second point, edges with date intervals, may have a bearing on a recent series of posts by Robert Cerny to the Topicmapmail list. (See: “Temporal validitity of subject indicators?” in the second quarter archives, early May 2011)

Is that timing for an association?

Tracking the relationships in Sex in the City would require such an ability.

5 Graph Databases to Consider

Friday, April 22nd, 2011

5 Graph Databases to Consider

General overview of Neo4J, FlockDB, AllegroGraph, GraphDB, InfiniteGraph.

InfiniteGraph 1.1 Release!

Saturday, February 5th, 2011

InfiniteGraph 1.1 Release!

From the website:

InfiniteGraph 1.1, the distributed graph database, was released today with a new indexing framework that gives users greater performance on indexing, data ingest and lookups. The improvements will help developers more quickly develop and deploy with InfiniteGraph, to process larger graph datasets and collections.

How much faster is this version? We’ve seen 100x faster performance in some scenarios, such as processing multiple indexed fields with large index sizes.


(general description of InfiniteGraph)

InfiniteGraph is a distributed, scalable graph database and developer API which enables large-scale graph processing, data analytics and discovery in systems and services developed around social networking, business intelligence, scientific research, national security and other advanced, mission critical requirements. InfiniteGraph offers a unique, graph database solution based on a highly-scalable, distributed data persistence technology that has been deployed in some of the most advanced and mission-critical enterprise and government systems in operation today. Organizations can use this solution to discover complex relationships in their data and develop applications with significant time-to-market advantages and technical cost savings.

On my short list of graph databases to evaluate in 2011 in connection with topic maps.

Not to mention also being folks I need to evangelize about topic maps.

Comments or suggestions on both of those tasks welcome!