In the world of databases, there are two main types: SQL and NoSQL. But what exactly is the difference between the two? A SQL database is a type of database that uses a structured query language (SQL) for storing, retrieving, and manipulating data. SQL databases are the most common type of database, and are used in a wide variety of applications.
A NoSQL database is a non-relational database that does not use the traditional SQL (Structured Query Language) to store or retrieve data. NoSQL databases are often used for big data applications that require a high degree of scalability and performance.
About SQL Databases
A SQL database is a relational database that uses Structured Query Language (SQL) to manage data. SQL databases are the most common type of database, and they are used in a variety of applications, including e-commerce, accounting, and customer relationship management (CRM).
SQL databases store data in tables, and each table has a unique key that identifies the table. Tables are linked together by relationships, and data is retrieved from the database by using SQL queries. SQL queries are used to select, insert, update, and delete data from the database.
SQL is a query language that is still widely used in relational databases. Relational databases are capable of storing data quickly and can handle complex queries. With a SQL database, you can efficiently store and access data which is structured. Structured data means that each piece of information has a relationship with other pieces of data. SQL is distinctly relational, it’s organized with tables and columns. The column data includes predefined items that are formatted in a specific way. With SQL, you need to organize the data beforehand.
About NoSQL Databases
As accessible data, types of storage and processing power as well as analytics have changed over the years, new database technologies have been created which are better suited for different use cases. These databases are called “NoSQL” and include Cassandra, MongoDB and Couchbase.
SQL databases are very helpful in a relational data structure. There’s little to no schema definition and users can accomplish multi-row transactions. NoSQL is more useful for cases without a predefined schema. Additionally, you can use NoSQL if your focus is to update unstructured data records.
With a NoSQL database, data can be stored in a format different than rows and columns. It provides more flexibility in the type of data that can be collected, and doesn’t necessarily mean that SQL is not used, as it often supports some SQL commands. More accurately, “NoSQL” is defined as a form of data storage that doesn’t use only SQL.
NoSQL systems allow for greater flexibility; you can work with different data structures within a database, like different types of documents or how people share their data. It is easier to make updates to these systems, so adding new attributes and fields won’t be difficult. NoSQL databases can both use varied syntax across databases and allow for a dynamic schema for unstructured data.
NoSQL databases scale in a way that’s more desirable than SQL. Because of sharding and high availability requirements, NoSQL databases can be grown horizontally. A good example is Cassandra, which handles massive amounts of data across many servers with no single points of failure and maximum availability.