Structured Query Language (SQL) is usually mentioned in relation to NoSQL. To better understand the difference between NoSQL and SQL, it may help to understand the history of SQL, the programming language used to retrieve specific information from a database.
Before the advent of relational databases, companies used a hierarchical database system with a tree-like structure for data tables. These early database management systems (DBMS) allowed users to organize large amounts of data. However, they were complex, often proprietary to a particular application, and limited in the ways they could reveal data. These limitations eventually led to the development of relational database management systems that organized data in tables. SQL provided an interface for interacting with relational data, allowing analysts to connect tables by joining common fields.
Over time, the requirements for faster and more diverse use of large data sets became increasingly important for new technologies, such as e-commerce applications. Programmers needed something more flexible than SQL databases (i.e. relational databases). NoSQL became an alternative.
Although NoSQL has become an alternative to SQL, this progress has by no means replaced SQL databases. For example, suppose you manage retail orders in a company. In a relational model, separate tables will separately manage customer data, order data, and product data, and they will be joined together using a unique common key such as a customer ID or order ID. While this is great for storing and retrieving data quickly, it does require a significant amount of memory. If you want to add more memory, SQL databases can only scale vertically, not horizontally, which means that your ability to add more memory is limited by the hardware you have. The result is that vertical scaling ultimately limits your company’s data storage and retrieval.
In comparison, NoSQL databases are non-relational, which eliminates the need for table joins. Their built-in sharding and high availability capabilities facilitate horizontal scaling. If a single database server is not enough to store all your data or process all your queries, the workload can be distributed across two or more servers, allowing businesses to scale their data horizontally.
While each type of database has its advantages, companies typically use both NoSQL and relational databases in the same application. Modern cloud providers can support either SQL or NoSQL databases. The choice of database depends on your goals.