SQL vs NoSQL Databases: How to Choose
SQL vs NoSQL explained by data shape and access pattern, with concrete examples for relational, document, key-value, wide-column and graph databases.
A database that stores data in tables of rows and columns and links related tables through shared keys, usually queried with SQL.
The relational model was described by Edgar F. Codd at IBM in 1970. In a relational database, each table holds one type of record, such as customers or orders, and relationships are expressed through keys. For example, each order row stores a customer ID that points to a row in the customers table. Popular systems include PostgreSQL, MySQL, Microsoft SQL Server, and Oracle Database.
Relational databases enforce structure and support transactions, which ensure that related changes either all succeed or all fail. This makes them well suited to accounting, inventory, bookings, and other systems where accuracy matters. An online shop deducting stock and recording a payment can rely on a transaction to avoid half-finished updates. NoSQL databases offer alternatives for flexible or very high-volume data.
A broad category of databases that store data in formats other than traditional relational tables, such as documents, key-value pairs, or graphs.
QueryA request for data or information from a database, search engine, or other system, usually written in a specific language or format.
SQLStructured Query Language: the standard language for storing, querying, and managing data in relational databases.
SQL vs NoSQL explained by data shape and access pattern, with concrete examples for relational, document, key-value, wide-column and graph databases.
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