Neo4j CEO talks growing enterprise graph adoption and why partnering with Google makes sense
By Diginomica - March 12, 2020
Explore: Adobe • eBay • emil eifrem • Fortune 500 • Orange • Volvo • Walmart
Powering Recommendations with a Graph Database: Proven Business Benefits [+ Case Studies]
By Jocelyn Hoppa
August 27, 2018 6 mins read
Relevant, real-time recommendations drive revenue, but they are challenging to deliver. That’s because good recommendations require bringing together so much data, surfacing the relationships between all that data and delivering just the right suggestion in context and in the moment.… Read more →
Explore: Connected Data • data architecture • eBay • graph database • pricing engine • rdbms • real-time recommendations • Recommendations • sql • Walmart
Retail & Neo4j: Personalized Promotion & Product Recommendations
By Bryce Merkl Sasaki
November 6, 2017 7 mins read
Today’s retailers face a number of complex and emerging challenges. Thanks to lower overhead and higher volume, online behemoths like Amazon can deliver products faster and at a lower price, driving smaller retailers out of business. In order to compete,… Read more →
Explore: Connected Data • Cyber Monday • ecommerce • graph technology • personalized promotion • product recommendations • real-time recommendations • Recommendation Engine • Retail • Walmart
How Walmart Uses Neo4j for Retail Competitive Advantage
By Bryce Merkl Sasaki
December 14, 2015 3 mins read
In a little over 50 years, Walmart grew from a small, family-owned business to become the world’s largest public corporation, with over 2 million employees and annual revenues of $470 billion. But Walmart didn’t just become the world’s largest retailer… Read more →
Explore: competitive advantage • ecommerce • graph database • neo4j • product recommendations • real-time recommendation • Recommendation Engine • retail competitive advantage • sustainable competitive advantage • Walmart