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Neo4j Breaks Scale Barrier with Trillion+ Relationship Graph

Neo4j Breaks Scale Barrier with Trillion+ Relationship Graph
Trusted to Scale by NASA, Meredith, ATPCO, and More; Neo4j Defines the Future of Enterprise Scale for Graphs with Distributed Architecture, Advanced Sharding, and Real-Time Performance

Neo4j Online Developer Expo & Summit – Neo4j, the leader in graph technology, demonstrated its super-scaling technology to show real-time query performance against a graph with over 200 billion nodes and more than a trillion relationships, running on over one thousand machines.

To put it into perspective, a graph of a trillion relationships could house a social graph detailing how every person on the planet is connected.

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Use cases driven by AI/machine learning and the relentless growth of enterprise data highlight the need for reliable, increasingly scalable graphs. Until now, a graph database housing over a trillion relationships has been impossible in most enterprise production environments. As customers expand their applications to include larger datasets with more relationships, they know they can trust the Neo4j graph data platform to scale to meet their current and future needs.

Neo4j thrives on user innovation and has built the largest team of graph experts on the planet, dedicated to providing breakthrough innovations in a standard graph query language, performance, security, and scale to the community so they’re empowered to change the world.

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Philip Rathle, VP of Products at Neo4j, shared his thoughts on Neo4j Fabric, the technology behind today’s demonstration. Neo4j Fabric enables data sets to be broken up and scaled horizontally without limits. Unlike other vendors, Neo4j’s approach to scaling graphs does not compromise read or write performance.

“Neo4j is excited to lead the way in definitively scaling graphs without compromise,” Rathle said. “Today’s demo showcases that it’s possible for a deeply interconnected data set to be sharded and deliver data scale. We’ve done this while maintaining millisecond response times with complex graph queries into the trillions of relationships, hundreds of terabytes, and thousands of machines. This feat is the result of years of scale and performance R&D. We’re looking forward to seeing how our customers innovate with this level of extreme scale and to evolve it even further.”

Neo4j Trusted to Scale by Enterprise Customers

Neo4j serves more than 800 enterprise customers who trust its technology to power mission-critical applications while maintaining security, performance, availability, and data integrity.

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Meredith Corporation, a leading media company, produces service journalism that engages audiences with essential, inspiring, and trusted content. With over 40 top consumer brands from PEOPLE to PARENTS, REAL SIMPLE, and Allrecipes, Meredith uses Neo4j to optimize how their digital presence reaches more than 190 million users a month and nearly 95% of all U.S. women across domains, apps, websites, podcasts, and video.

Cameron Harmon, Data Scientist at Meredith Corporation, shared how the company has scaled its Neo4j graph to analyze 30 billion nodes of digital traffic and has tested capacity to comfortably accommodate 100 billion in the future.

“With millions of views and millions of unique visits per month across different topics and lifestyles, our consumers trust us for information on things that affect their daily lives, as well as pique their interest. By understanding and analyzing this content and how it’s consumed, we strive to provide the best experience for both our audiences and advertisers alike.”

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Long-standing customer ATPCO has implemented a Neo4j-powered pricing engine for airfare pricing. Neo4j is at the core of several data services offered, from fare management to air travel tax calculation. Setting a competitive price for 99% of the world’ airfares involves a large amount of complex data processing, featuring:

  • Over 100 billion product permutations
  • Five primary data services provided to 427 airlines
  • Millisecond response times

“NASA has over 50 years of data, d***** back to the Apollo and Gemini eras. Based on what I have seen, billions of nodes and relationships will not be an issue with Neo4j.” – David Meza, NASA.

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