NoSQL (Not Only SQL) is a type of database for web applications and big data which allows users to store and retrieve information in a format that is intuitive and easy to understand. Instead of complex tables or data, NoSQL stores information as ASCII text and manipulates it with built-in operators. Leveraging cloud computing to eliminate downtime, NoSQL provides mechanisms different from the fixed tables, columns, and rows used in relational databases.
The name “NoSQL” was first used in 1998 to identify Carl Strozzi’s Strozzi NoSQL open-source relational database. NoSQL databases are flexible, scalable, non-tabular, and non-relational, embracing simplicity in design to provide developers with flexibility in scaling big data. They feature agile schemas that offer efficient functionality and high performance and availability.
A common misconception of NoSQL is that it does not support SQL-like queries. To the contrary, NoSQL can actually stand alongside SQL databases, as they stores relationship data differently from traditional databases. Users can stock related data in a single structure without the need to split them between tables.
With their simplicity and scalability, NoSQL databases are developer-friendly. As cloud computing offers cost-efficient hosting of data and applications, the volume of data and queries also grows. Software engineers can quickly adapt to fast-changing data requirements. It allows developers to store large amounts of unstructured data and enable data distribution across multiple servers.
There are four types of databases to choose to make managing large volumes of data and user loads easier:
Structured query language (SQL) databases — like Oracle SQL Developer, IBM Db2, Microsoft SQL Server, or the open-source MySQL — are traditional and popular relational databases that store data in tables with fixed rows and columns. Storage and retrieval is accomplished by the application negotiating the tabular relationships between data.
SQL databases demand more processing resources and time. Before starting the development, database and software engineers must plan their projects to the minute details, creating complex E-R (entity-relationship) diagrams to reduce data duplication.
SQL databases feature standardized interfaces, while NoSQL databases prefer accessibility, tolerance to partition, and speed over standardization.
One advantage of NoSQL over MySQL is the flexibility of its design schema. SQL relational databases, requires a detailed database model. With NoSQL, which is naturally non-relational, it is easier to scale to meet the demands of big data by adding using documents. MySQL has a standard query language that NoSQL might lack.
Examples of NoSQL databases include MongoDB and CouchDB.