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Posted January 15, 2014

Neo4j 2.0 Aims to Bring Graph Databases to the Masses

By Darryl K. Taft

Neo Technology, maker of the Neo4j graph database, has released Neo4j 2.0, which the company says will help bring graph databases to the masses.

Neo announced an online training program along with the new release to help make the technology more approachable for mainstream users.

A graph database is a database that uses graph structures with nodes, edges and properties to represent and store data. Every element in a graph database contains a direct pointer to its adjacent element, and no index lookups are necessary.

Emil Eifrem, CEO of Neo Technology, said he believes Neo4j 2.0 is the most substantial piece of engineering ever invested in the graph space, and will catapult graphs to the mainstream.

"Five years from now we will look back on Neo4j 2.0 and think that's when it began," he said in a statement. "That was the pivotal point when graphs started becoming a tool on equal footing with SQL and MapReduce for data management."

Eifrem noted that industry influencers have begun to acknowledge the growth of the graph database market. A recent 451 Research report says, "The graph database and graph analysis sector is beginning to come into its own."

Matt Aslett, research director for data management and analytics at 451 Research, said, "We are seeing increased interest in graph databases as enterprises understand the potential use-cases and recognize that they have 'graphable' business problems. Neo4j and Neo Technology are at the forefront of driving that increased interest and understanding."

While the rise of graph databases is closely linked to the increasing popularity of social networking sites like Facebook, Twitter and LinkedIn, graphs are now recognized as playing an important role in solving a lot of seemingly intractable technology problems across a broad range of industries and use cases, Eifrem said. Today, Neo4j is used by graph innovators around the world for a wide variety of projects, in a variety of industries, ranging from BangWithFriends.com to National Geographic.

Eifrem said he began working on graph database technology more than a decade ago in Sweden, where he was working with a team of 20 engineers and 10 of them seemed to always be busy tweaking the relational database management system to do what they needed.

"We looked for a database that worked with connected data," he said. "We couldn't find one so we decided to build our own. That was back in 2000."

Thus, Neo4j represents several years' worth of R&D efforts, with this latest version making it possible for anyone to install, learn and harness the power of the graph. Neo4j 2.0 includes radical improvements to Cypher, Neo4j's purpose-built graph query language, and includes a new visual interactive UI.

New features include a labeled property graph. Neo4j 2.0 introduces a new schema construct, labels, to its data model. Labels greatly speed development. They enable developers to tell the database more about the data, allowing the database to do more for the developer. New label features include automatic indexing and unique constraints.

The new release also introduces Cypher 2.0. Cypher is a popular way to access graph data today. Neo4j 2.0 adds new capability to Cypher, making it easy to develop graph applications with much less code than in SQL.

"Our Neo4j solution is literally thousands of times faster than the prior MySQL solution, with queries that require 10 to 100 times less code," said Volker Pacher, a senior developer at eBay, in a statement. "At the same time, Neo4j allowed us to add functionality that was previously not possible."

The new release also features the Neo4j browser, a new interactive query environment that enables rapid prototyping of Cypher queries and visual data discovery.

Neo announced that Zephyr Health, a big data analytics platform for companies in the life sciences industry, is using Neo4j. Neo4j enables Zephyr Health users to be "their own data scientist" with the ability to discover new connections between data from disparate sources with a graph database that can rapidly adapt to a changing business.

 


Originally published on eWeek.

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