Building on Multi-Model Databases

Chapter 2. The Rise of NoSQL

In early 2009, Johan Oskarsson organized an event to discuss “open source distributed, nonrelational databases,” during which he and a friend coined the term NoSQL (not SQL). The acronym attempted to label the emergence of an increasing number of nonrelational, distributed data stores, including open source clones of Google’s BigTable/MapReduce and Amazon’s Dynamo.

The rise of these systems can be attributed to the rise of big data; the volume, variety, and velocity of data in industries began rapidly increasing with the rise of the internet and the increase of power and proliferation of mobile and computing devices. Rows and columns alone weren’t going to cut it anymore, and so new systems emerged to tackle some of the use cases for which traditional relational approaches were no longer a good fit for the data models or fast enough or scalable enough to meet the increased demand.

NoSQL technologies might not be databases in the traditional sense, meaning that many of them do not provide both transactional integrity and real-time results, and some of them provide neither. Each resulted from an effort to alleviate specific limitations found in the RDBMS world that were preventing their architects from completing a specific type of task, and they all made trade-offs to get there. Whether it was tackling “hot row” lock contention, horizontal scale, sparse-data performance problems, or single-schema induced rigidity, they are much more narrowly focused ...