Garrett Eardley explores how Riot Games is leveraging Riak for their stats system, discussing why they chose Riak, the data model and indexes, and strategies for working with eventually consistent data.
Andy Gross reflects on five years of involvement with Riak and distributed databases and discusses what went right, what went wrong, and what the next five years may hold for Riak.
Shanley Kane discusses Dynamo - consistent hashing, vector clocks, hinted handoff, gossip protocol - advances in each area, and how querying and application development has changed as a result of them.
Jesse Newland discusses how GitHub pages were re-written with Erlang, Riak and Webmachine in order to improve their performance.
Justin Sheehy discusses designing reliable distributed systems that can scale in order to deal with concurrency problems and the tradeoffs required by such systems.
Andy Gross reports on how Basho used Riak and Erlang to build their cloud storage service.
Kresten Krab Thorup discusses bringing Riak to mobile. He covers Riak’s data model, BucketDB – a Riak client-, and the protocol used to synchronize the data on the device between BucketDB and Riak.
Susan Potter discusses Dynamo, Riak, distribution, consistency and fault tolerance, along with techniques and an example for building an application with riak_core.
Bob Ippolito explains how to solve concurrent update conflicts with Statebox, an open source library for automatic conflict resolution, running on top of Riak.
Sean Cribbs explains what Map-Reduce and Riak are, why and how to use Map-Reduce with Riak, and how to convert SQL queries into their Map-Reduce equivalents.
Shaneal Manek tells the story of how things can go wrong with a distributed system which turned into a success after incorporating appropriate tools for monitoring, analytics, logging, security.
Kresten Krab Thorup discusses data models for Riak, a protocol for synchronizing key-values, and BucketDB, a mobile Riak client.