In this interview at QCon London, LinkedIn’s Sid Anand discusses the problems they face when serving high-traffic, high-volume data. Sid explains how they’re moving some use cases from Oracle to gain headroom, and lifts the hood on their open source search and data replication projects, including Kafka, Voldemort, Espresso and Databus.
On September 29th LinkedIn Signal was announced, providing a social search application both for LinkedIn shares and tweets from LinkedIn-Twitter bounded accounts. This article aims to provide more insight into the motivation and technical challenges of combining Scala, JRuby and Voldemort, at such scale.
Lars George and Fabrizio Schmidt present Germany’s largest social networks, Schuelervz, Studivz and Meinvz, the problems they are facing daily, the architecture used in the past and the need to move to a NoSQL solution. The presentation concludes with lessons learned and plans for the future.
Geir Magnusson explains how Gilt Groupe is using Project Voldemort to scale out their e-commerce transactional system. The initial SQL solution had to be replaced because it could not handle the transactional spikes the site is experiencing daily due to its particular way of selling their inventory: each day at noon. Magnusson explains why they chose Voldemort and talks about the architecture.
Jay Kreps discusses the architecture, algorithms, implementation and deployment of Voldemort, a distributed storage system. He also presents the problems solved using Voldemort at LinkedIn.
