The table below describes their differences in terms of database structure, storage model, scalability, properties, support, and communities. To make informed decisions about which database type to use, practitioners should know the differences between SQL and NoSQL. NoSQL databases can be quicker to develop applications with, can offer more flexibility and scale and they often offer excellent performance due to their specialised nature. Typically, these databases are built for the web or for scenarios where traditional relational databases can have limitations. This database category aims to build flexible schemas and specific data models. NoSQL stands for “not only SQL” rather than “no SQL”. This is the reason why NoSQL is the popular database category alternative to traditional RDBMS.

The main difference between NoSQL and SQL is that NoSQL adopts a ‘right tool for the job’ approach, whilst SQL adopts a ‘one tool for all the jobs’.

NoSQL is one of these newer database systems. This is mainly due to the rising volume of unstructured data, changing storage requirements, the need for high processing power, and evolving requirements in analytics that database applications have to cater to. While SQL remains a standard in organisations worldwide, we see many other database systems emerging. Its primary focus was to reduce system data duplication by creating data structures and schemas. The SQL database language emerged back in 1970. Many IT decision-makers, developers and analysts are familiar with the Relational Database Management System (RDBMS) and the structured Query Language (SQL). This article will explore the difference between SQL and NoSQL and which option is best for your use case. They can be divided into two primary categories: SQL (relational database) and NoSQL (non-relational database). There are scores of open source and proprietary databases available, and each offers distinct value to organisations. IT leaders, engineers, and developers must consider multiple factors when using a database.

Non tabular database