For all of the 1990s and most of the 2000s, database management was synonymous with the relational database. By the end of the 1990s, the relational database management system (RDBMSs) used the SQL language, relational data model, and ACID transactions to provide a one-size-fits-all-solution for data management.
It’s been clear for at least 5 years that the relational database—though still the dominant model—is not the only game in town. Starting around 2008, a variety of “NoSQL,” “NewSQL” and “big data” technologies emerged that are tailored to more specific workloads. These include big data technologies such as Hadoop and Spark, operational “web scale” NoSQL databases such as MongoDB and Cassandra, and “NewSQL” systems such as HANA and Vertica.
The suddenness of this non-relational “breakout” created a lot of noise and confusion and—at least initially—an explosion of new database systems. However, the database landscape is settling down, and in the past few years, the biggest meta trend in database management has been a reduction in the number of leading vendors and consolidation of core technologies. Additionally, we’re starting to see database as a service (DBaaS) offerings become increasingly credible alternatives to on-premise or do-it-yourself cloud database configuration.