Enterprises today, no matter what industry, are all looking to technology solutions to help them gain a leg up on the competition. First and foremost, these technologies should be as flexible and agile as the modern development practices that support them. That’s one of the reasons behind the rise of NoSQL databases in replacing old relational database technology. NoSQL databases provide the performance, scale, and flexibility required of modern applications.
But that is where the similarity between NoSQL systems end. The only thing most NoSQL databases have in common is that they do not follow a relational data model. NoSQL databases typically fall into one of four categories:
- ** Key-value stores ** are the simplest. Every item in the database is stored as an attribute name (or "key") together with its value. Riak, Voldemort, and Redis are the most well-known in this category.
- ** Wide-column stores ** store data together as columns instead of rows and are optimized for queries over large datasets. The most popular are Cassandra and HBase.
- ** Document databases ** pair each key with a complex data structure known as a document. Documents can contain many different key-value pairs, or key-array pairs, or even nested documents. MongoDB is the most popular of these databases.
- ** Graph databases ** are used to store information about networks, such as social connections. Examples are Neo4J and HyperGraphDB.
Companies are finding that they can apply NoSQL technology to a growing list of use cases while saving money in comparison to operating a relational database. NoSQL databases are designed to scale horizontally across many servers, which makes them appealing for large data volumes or application loads that exceed the capacity of a single server.
MongoDB is the most popular of all NoSQL database as it preserves the best features of relational databases while incorporating the advantages of NoSQL. To learn more about why MongoDB is the most widely-used NoSQL database, read our free white paper, “Top 5 Considerations When Evaluating NoSQL Databases.”