Jargon Buster: What's the meaning of NoSQL database?

While SQL (Structured Query Language) is designed for managing data held in a relational database management system, the most fundamental choices to make when developing an application is the use of an SQL or NoSQL database to store the data.

Originally based on relational algebra and tuple relational calculus, SQL are designed for reliable transactions and ad hoc queries, the staple line of business applications.

NoSQL, also called "Not only SQL" to emphasize that they may support SQL-like query languages, are increasingly used in big data and real-time web applications. It's a response to the limitations of the SQL systems, and it can store and manage data in ways that allow for high operational speed and great flexibility on the part of the developers.

The NoSQL databases have existed since the late 1960s, but did go by the moniker (NoSQL) until a surge of popularity in the early twenty-first century, triggered by the needs of Web 2.0 companies.

The term NoSQL was first used by Carlo Strozzi in 1998 to name a lightweight open-source relational database that did not expose the standard Structured Query Language (SQL) interface, though still relational, and quite distinct from the circa-2009 general concept of NoSQL databases.

The data structures used are viewed as "more flexible" than relational database tables, with suitability of the database depending on the problem it must solve.

Fundamentally, the difference between SQL and NoSQL is that each has a different philosophy for storage and retrieval of data. And Many NoSQL stores compromise consistency in favor of availability, partition tolerance, and speed.

Albeit, some applications still call for the kinds of constraints, consistency, and safeguards that SQL databases provide, which supposedly “advantages” of NoSQL may turn to disadvantages for such use case.

Other disadvantage of NoSQL is the relative lack of expertise, and the rather nascent market for the database system.

But SQL and NoSQL systems will still have their place for many more years to come, even as there are signs that future generations of databases may thread the paradigms and offer both NoSQL and SQL functionality.
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