Xconomy takes a close look at evolution of databases with Emil Eifrem, CEO of Neo Technology and why businesses should be exploiting connected data.

It’s pretty clear that the biggest winners in Silicon Valley in the past decade have been the companies that understood and exploited connections—between Web pages, in the case of Google, or between people, in the cases of Facebook, LinkedIn, and Twitter. To build their empires, all of these companies had to painstakingly develop several new types of databases capable of representing and sorting through such connections. One type is called a graph database. I wrote about an important example, Google’s Knowledge Graph, back in December. Neo’s database, called Neo4j, is the first commercial, off-the-shelf graph database. Any company can use it; no longer do you have to build your own graph database to take advantage of connected data. Do I have your attention yet? “There are two types of data: atomic data about single individuals, and connective data about how various elements are connected,” argues Neo’s co-founder and CEO, Emil Eifrem. “There are a bunch of industries that have only exploited atomic data so far. And what we are seeing—what has played out in several industries—is that when a guy or girl comes along who starts exploiting the connections, it revolutionizes that industry.”

Neo CEO Emil Eifrem uses a whiteboard to explain graph databases.

Of course, every startup CEO talks about how his company’s technology is revolutionizing the world. But Eifrem, an uncharacteristically brash Swede, goes even farther. He thinks the companies that fail to understand the connections in their data will inevitably be left behind. “Whoever you are, you are eventually going to have to exploit connected data in your industry, or you are going to go out of business, because somebody else will,” he says. For many applications, analyzing connections at large scale means abandoning the relational database model that has dominated the computer industry for the last 40 years. It’s not that relational databases can’t hold connective data; they’re just not very good at it. Neo4j, by contrast, was designed from the ground up to represent relationships between entities, right down to the way the data is recorded on a disk. To see the power of a graph database, consider this example. Eifrem says a big social network that he isn’t allowed to name approached his company to ask for a demonstration of Neo4j. It handed the startup a sample dataset representing 1,000 people connected in a network; each person had an average of 50 friends. Read the full article.