Neo4j serves up real-time recommendations for market leading retailers, as well as some of today’s most popular online dating and job sites

Anyone who has shopped on Amazon.com is familiar with the “You may also like” phrase. Today, companies across a range of industries—from retail to online dating to financial services—are taking a nod from Amazon by implementing technology to offer real-time suggestions to their online consumers. Creating an online recommendations system, however, requires a new generation of technology. Enter Neo Technology, creator of Neo4j, the world’s leading graph database, which has quickly become the de facto technology for powering recommendations among market leaders such as Wal-Mart and eBay.

“Automatically generated recommendations allow businesses to maximize the value they deliver to their online consumers. The ability to offer a flexible and personalized relationship could be considered one of the most important technology innovations that benefit both consumers and brands,” said Emil Eifrem, founder and CEO of Neo Technology. “The biggest criterion for recommendation systems—apart from accuracy—is speed. The analysis must be done in real-time before the customer moves on to a competitor’s website. This is where relational databases come up short.”

Traditional Relational Database Management Systems (RDBMS) are not meant to collect data and seek out relationships among individual data points, given their design. Graph databases, in contrast, are suited to handle both data as well as data relationships with far more ease as they model, store and query the data using graph oriented constructs – revealing valuable insights from data relationships. While relational databases will often deteriorate in performance over time as a data set grows both in size and connectedness, which can make them quite slow, graph databases offer consistent performance regardless of the size and density of connections.

Neo4j: The Graph Database That Powers All Types of Recommendations

Recommendation systems using graph databases help companies personalize product, content and services offers by leveraging the intelligence available from the connections within their data. With Neo4j, companies are able to tap into this insight, particularly for areas such as:

Product Recommendations: Wal-Mart considers Neo4j “a perfect tool for real-time product recommendations” and is using Neo4j to make sense of online shoppers’ behavior in order to be able to optimize-up and cross-sell major product lines in core markets. The retailer has sales of more than $460 billion and employs 2.2 million associates worldwide, serving more than 245 million customers weekly at its 11,000 stores in 27 countries and on its e-commerce websites in 10 countries.

Courier Routing: eBay uses the Neo4j graph database for sophisticated, real-time courier/package routing. “We found Neo4j to be literally thousands of times faster than our prior MySQL solution, with queries that require 10-100 times less code. Today, Neo4j provides eBay with functionality that was previously impossible,” said Volker Pacher, Senior Developer at eBay.

  • Healthcare: Recognized as the industry leader in patient management for discharges and referrals, Curaspan Health Group connects providers, payers and suppliers via secure electronic patient-transition networks to improve outcomes as patients move between levels of care. With Neo4j, the company is able to satisfy complex Graph Search queries, such as “Find a skilled nursing facility within n miles of a given location, belonging to health care group XYZ, offering speech therapy and cardiac care, and optionally Italian language services.” The power of the graph database allows Curaspan to provide the best possible referrals for more than 4,600 healthcare facilities, and tens of thousands of patients throughout the U.S.
  • Online Dating: Online dating firm SNAP Interactive is the company behind the popular site “Are You Interested,” with 68 million users. SNAP understood that relationships are more successful if they are forged between people who have friends in common. In order to improve its real-time dating recommendations, SNAP sought to identify its users’ common friends and friends-of-friends – effectively leveraging 10 billion connections across its database of over one billion unique users. Before adopting Neo4j, SNAP Interactive had no efficient way to gather this data.
  • Movie Recommendations: A leading movie recommendation website is revolutionizing the way the film industry promotes projects by enabling fans to discover the best upcoming releases before they hit the big screen, and make recommendations based on individual taste. In turn, it provides movie studios with insights into the preferences and behavior of film fans, enabling them to more effectively target their marketing campaigns. The company considered MySQL databases for its recommendation system, but after seeing the amount of data required, looked at other databases and chose Neo4j.

  • Shopping Recommendations: Cobrain makes personalized shopping recommendations to consumers from the products offered by more than 300 major apparel merchants. Members spend a few moments telling Cobrain what they like. It then uses Neo4j to make billions of calculations in order to find the products loved by their anonymous cohorts and provide real-time recommendations.

Business Benefits of Neo4j

Across industries, Neo4j offers:

  • Improved competitiveness: Neo4j enables new types of business functionality that is often not possible with other technologies, allowing consumers to make real-time decisions based on connected data.

  • Reduced project time, complexity and cost: Neo4j cuts the overhead on many types of projects, particularly those involving connected data. Many customers cite the huge acceleration that occurs when a graph model is brought to bear on a connected data problem.

  • Faster project time to market and better performance: Neo4j requires developers to produce less code than relational DB alternatives. Less code equates to higher quality and an increased success rate on projects. Neo4j’s performance is dramatically better for connected data sets – often the difference between something being possible and not possible.

 

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