Finally, "big data" isn't exactly right because you don't need large data sets to take advantage of databases that fit your data more naturally than relational databases. "Nonrelational" doesn't quite apply, either, because graph databases are very relational; they just track different forms of relationships than traditional RDBMSes.
In truth, these are the rest of the databases that solve the rest of our problems. The marketing noise of past decades combined with hardware and bandwidth limitations, as well as lower expectations in terms of latency and volume, prevented some of the older kinds of databases from reaching as wide notoriety as RDBMSes.
Just as we shouldn't try to solve all of our problems with an RDBMS, we shouldn't try to solve all of our math problems with set theory. Today's data problems are getting complicated: The scalability, performance (low latency), and volume needs are greater. In order to solve these problems, we're going to have to use more than one database technology.
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