Main difference between SQL and NoSQL

SQL databases are general-purpose, but NoSQL databases are designed for specialized use cases. The key comparisons between NoSQL and SQL may be summarized as follows: Schema Requirement, scalability, data model, API, and integrity. Each takes a unique approach to all of these elements in data retrieval.

Schema:- A NoSQL database’s schema is flexible, which means that there is no predefined layout for the data and data types. Data can be stored in a schema-less or free-form format. This technique provides programmers with greater freedom, which can save development time.

Scalability:- Horizontal expanding, also known as expanding out, is commonly used in NoSQL databases. Expanding out means adding extra hardware to a structure, most commonly in the form of more commodity servers. Horizontal partitioning with sharding is commonly used in NoSQL systems to divide up huge databases into smaller parts dispersed across multiple servers. The SQL strategy is often vertical scaling, also known as scaling up. Vertical scaling adds more resources, such as a more powerful CPU or more memory, to manage greater demand or enhance performance.

Data model: Data is not structured as tables with defined rows and columns in NoSQL database systems, as it is in SQL DBMS. Data can instead be represented as graphs with nodes and edges and JSON documents or key-value pairs, depending on the NoSQL database. The table and row idea are used in wide-column storage, although columns can be flexible from row to row inside a table.

API: Even though many NoSQL databases include a SQL-like query language, SQL is not necessary as an Application Programming Interface also known as “API” to the data in the database. SQL is often the primary interface to the data in SQL databases.