LinkedIn

This article is part 2 in a series about LinkedIn’s data journey. You can read the first part of LinkedIn’s data infrastructure here.  It requires repeating that LinkedIn is a

LinkedIn has become a staple for the modern professional, whether it’s used for searching for a new job, reading industry news, or keeping up with professional connections.  As a

A large social network needs to develop systems for ingesting, storing, and processing large volumes of data. Data engineering at scale requires multiple engineering teams that are

LinkedIn is a social network with petabytes of data.  In order to store that data, LinkedIn distributes and replicates that data across a large cluster of machines running the Hadoop

Apache Kafka was created at LinkedIn. Kafka was open sourced in 2011, when the company was eight years old. By that time, LinkedIn had developed a social network with millions of users.