Dzone interviews Dr. Jim Webber, Chief Scientist at Neo Technology about the excitement around graph databases and upcoming event: GraphConnect 2012 in San Francisco.

In less than a week, a group of developers (which can still include you at a discount!) will gather in San Francisco to talk with some of the world’s experts on Graph Databases and their many practical applications in computing.  This will be during the Graph Connect conference, the first conference focused solely on graph theory and graph technology.  Sessions will range from high-level to very specific use cases while still providing practical guidance on graph databases like Neo4j and graph processing techniques.

I recently talked with Dr. Jim Webber, the chief scientist at Neo Technology, to get some insights into the current events around graph databases and some background on the the widespread growing interest in graph dbs.  Neo Technology is the company organizing the Graph Connect conference.

Neo4j – Graph Database Admin, Even Non-Technical Users

I asked Dr. Webber about the recent advances made in Neo4j 1.8 and he gave me an overview of new features divided by those that were new to the database engine and those that were visible to users.

Under the covers, he said, there were many improvements to the engine and the traversal framework, which is now faster on denser graphs.

On the surface,  the main query languagefor Neo4j, called Cypher, now has tools and usability features that allow even non-programmers to understand and modify the graph database’s structure.  Previously, Dr. Webber says predominantly programmers understood and took advantage of the full expressiveness of graph models in Cypher since it required some knowledge of low level code.

But now Dr. Webber says that if you can sketch the graph on a whiteboard, you can use Cypher and create the model.  He told me that the community around Neo4j would continue to build on this this abstraction in Cypher for future releases.

I also asked Dr. Webber about the peak scalability limits on Neo4j.  He said that they’ve seen use cases in the single-digit billions in terms of node count.  So for now they’ve kept the filesystem max at 34 billion nodes, leaving headroom for all use cases thus far.  In the future, if there is a need they will always be able to add more bits on the filesystem.  That’s when you’d have to discuss the tradeoff between bites on the filesystem and footprint on disk vs. the realistic headroom for nodes, relations, and properties.

Graph Theory – Still Alive

Graph theory is 275 years old, Dr. Webber told me, and it’s not a dead branch of science.  There is still plenty of active research going on in psychology, math, sociology, and computing of course.  Not only are the models of Graph Theory more expressive models in many cases, but they are also excellent at predictive analysis.

The great thing about using graph data sets, Webber says, is being able to refer back to the centuries of graph theory and discrete math that’s already been done in the field.  The properties are well known, so if you find and apply these properties, you’ll get plenty of initial insights.

Relational vs. Graph Thinking

I told Dr. Webber that many of the developers I talk to about graph databases find that graph models were more intuitive to them, and he agreed that graph databases can be very intuitive to those who aren’t tainted by the mainstream business information systems approach throughout the industry, which seems to have wired developers’ minds around tables.  Most who try graphs never want to go back, and Dr. Webber can attest that he definitely would curse a lot more when he was working with relational dbs, simply because it was so hard to get little things done sometimes.

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