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.
Neo4j 2.0 Aims to Bring Graph Databases to the Masses
“There is a revolution happening in big data analytics, creating demand for business users to be their own data scientist,” said Brian Roy, director of platform engineering and architecture at Zephyr Health, in a statement. “In development of the Zephyr analytics platform, we found Neo4j to be the best open solution that met our needs, offering flexibility, scalability and a viable community committed to creating the building blocks that accelerate our business.”
Zephyr Health uses Neo4j to enable its cloud-based Zephyr analytics platform, providing graph analytics across a diversity of data. The Zephyr analytics platform allows pharmaceutical makers, medical device manufacturers and other health care customers to discover connections across their data that can advance their R&D, clinical trials and marketing. For instance, Zephyr’s engine helps pharmaceutical companies find the right doctors for a clinical trial by linking private and public data—such as specialty, geography and clinical trial history.
Zephyr Health’s vision was to create a platform that would unify data in a way that could provide customers with deep insights into the dynamics of a given market. For this, Zephyr needed to combine a wealth of data from both its customers and public sources of information. It then needed to build an application capable of querying this mix of multisourced data. Two factors caused Zephyr to look beyond traditional database technologies for its solution. First was the real-time analytic component: making sense of connections across these diverse sets of data in real time. The second was the diverse and changing nature of their data, for example with data from doctor’s surveys, which caused new attributes to come in regularly.
Zephyr solved this problem by storing the connected data in a Neo4j graph and exposing it to business users via its own domain query language. In a week or two of development, the Zephyr team was up and running with data on millions of physicians and hospitals. The company is now seeing its customer base and data volumes grow exponentially. The Zephyr analytics platform is running faster than expected and meeting and exceeding market demands.
“Graph databases are effective for every industry we know of—from telco and financial services, to logistics and hospitality, to online dating and health care,” Eifrem said. “The success that Zephyr Health has seen with Neo4j underscores the transformative business power that results when graphs are made available to everyone.”
Eifrem said there are primarily two types of organizations that are likely to use graph databases: big Web properties and commercial vendors.
He said attention paid to graph databases from larger, more established players like IBM, Oracle and Teradata sheds light on the technology, which stands in Neo’s favor.
Teradata announced its Teradata Aster SQL-GR graph engine late last year. The Aster SQL-GR engine enables native processing of large-scale analytic graph queries and prebuilt graph functions and can be used for customer churn, product affinity, fraud detection and recommendation engines. For example, telecommunications providers can use graph analysis to look for high-traffic connections among selected users, which provides clues to fraudulent calling activity. Eifrem said financial services institutions, particularly investment banks, are using Neo4j to analyze fraud as well.
Eifrem said Neo4j has a leg up on bigger players like Teradata because of its maturity and robustness.
“Databases require calendar time to be robust,” he said. “It takes time. These guys are all new. We’ve been running 24/7 production for eight years. We also have an ecosystem advantage over everyone else. We’re much more popular than the others out there.”
Database monitoring site DB-Engines ranks Neo4j as clearly the most popular graph database available today, Eifrem said.