NoSQL databases arose as an answer to the innovation-stifling limitations of traditional relational databases. Developers needed databases that adopted modern advantages of cloud computing and cheap hardware. They also needed databases that were built with agile software practices in mind. And enterprises wanted technology that could handle the challenges of Big Data and the three V’s of data – volume, variety and velocity of data.
NoSQL technologies were born of these demands but they are all different in their approaches. The term “NoSQL” is really an umbrella for any database that doesn’t following the relational model. Still, you can cast most NoSQL databases into one of four buckets:
- ** Key-value stores ** which stores data as an attribute name together with its value. This is the simplest type of NoSQL database and Riak, Voldemort, and Redis are the most popular.
- ** Wide-column stores ** structure data together in columns. Cassandra and HBase are the most well-known in this category.
- ** Document databases, ** such as MongoDB, store data in documents.
- ** Graph database ** such as Neo4J and HyperGraphDB are particularly useful for data about networks such as social connections.
If you’re looking for a high-performing database with applicability across many different use cases, then MongoDB is the database to choose in a crowded field of options. MongoDB is the most popular NoSQL databases according to the DB-Engines rankings. Over a third of the Fortune 100 choose MongoDB for their operational applications because of its strong enterprise offerings.
To learn more about why MongoDB is the most widely used NoSQL database and for a general NoSQL vendor comparison download the free white paper.