NoSQL databases came about as an answer to the innovation-stifling limitations of traditional relational databases. Developers needed databases that took advantage of innovations in cloud computing and commodity hardware. They also needed databases that aligned with modern iterative software practices and that could handle the volume, variety and velocity of Big Data applications.
NoSQL technologies were born of these requirements but that’s where their commonality ends. NoSQL database vary greatly but they typically fall within four types:
- Key-value stores have every single item in the database stored as an attribute name together with its value. This is the simplest type of NoSQL database and Riak, Voldemort, and Redis are examples.
- Wide-column stores. Data is stored together in columns. Cassandra and HBase are examples.
- Document databases store data in documents. MongoDB is the most well-known document database.
- Graph database are particularly useful for data about networks such as social connections. Neo4J and HyperGraphDB are examples.
MongoDB is a document database that leads the pack of NoSQL databases according to the latest DB-Engines rankings. In fact, organizations around the world, from Fortune 100 enterprises to the most agile startups, choose MongoDB for their operational applications. MongoDB incorporates the best of what relational databases have to offer along with the innovations that make NoSQL so popular today.
For a NoSQL databases comparison and to learn more about why MongoDB is the most widely used one, download the free white paper.