Meet up

The graphs of gaming and recruitment

Wednesday, 30th April at Skills Matter, London

This meetup was organised by Neo4J User Group in April 2014

Overview

Modelling a large scale social game with Neo4j

Learn how Gamesys did it by leveraging graph database Neo4j to model the in-game economy of our MMORPG “Here Be Monsters” and automate the balancing process.

We'll discuss lessons learned, successes and challenges, and how a graph database enables our small team of game designers to stay agile and focused on delivering new content to players.



Yan Cui

Yan is an experienced engineer who has run production workload at scale in AWS for nearly 10 years. He has been an architect and principal engineer with a variety of industries ranging from banking, e-commerce, sports streaming to mobile gaming. He has worked extensively with AWS Lambda in production, and has been helping various UK clients adopt AWS and serverless as an independent consultant.


Zerograph

Zerograph is an alternative server container for one or more Neo4j graph databases that uses ZeroMQ for fast and reliable communication and comes bundled with a Python client.



Nigel Small

Having begun BASIC programming on a Dragon 32 in 1983, I have always had a keen interest in technology. Over the past fifteen years, I have worked mainly in back-end system development and data management.


Private Social Networks

He’ll cover some of the lessons a small startup has learnt along the way.

He’ll cover some of the modelling pitfalls, how to deal with time, multi tenancy and sentiment. He’ll also talk through hosting and extending neo4J through managed server extensions.

Finally Matt will briefly touch on some more advanced topics like centrality, transitivity and how someone you have never met can make you fat.



Matt Wright

Matt Wright is the CTO at Stitched.io, a startup that aims to help build better teams using graph technology and machine learning. He's a mentor at the Barclays Techstars accelerator, and has been developing graph applications with machine learning for the last couple of years. Previously he worked in Investment Banking and helped build some of the genetic algorithms that lead to the credit crunch, but please don't hold that against him.


Who's coming?

Attending Members