Handling Billions Of Edges in a Graph Database

Hosted by San Francisco Bay Area Big Data and Scalable Systems

Public group


Modern graph databases are designed to handle the complexity but still not for the amount of data. When hitting a certain size of a graph, many dedicated graph databases reach their limits in vertical or, most common, horizontal scalability. In this talk, I'll provide a brief overview of current approaches and their limits towards scalability. Dealing with complex data in a complex system doesn't make things easier... but more fun finding a solution. Attendees will learn about existing challenges when scaling graph databases, current solutions to solve these challenges and the efficiency of current solutions.

About the speaker:

Dan Larkin is a theoretician turned practitioner. In his academic career, he worked for about seven years to design, analyze, implement, and experimentally evaluate a number of complex and novel data structures. He turned to the start-up world for a change of pace, where, frustrated with many of the NoSQL and graph database offerings he had attempted to use over the years, he found ArangoDB. He dropped what he was doing to join the ArangoDB team and has been happily working on the database internals ever since.