In a relational database, how is data stored in different tables brought together?

In a relational database, data is organized into tables, and when it’s necessary to combine data from these different tables, the process used is known as joins. Joins enable the relational database management system to effectively relate data stored in separate tables based on a common field or key. This allows for complex queries that can pull information from multiple sources, giving a comprehensive view from disparate data sets.

Joins can take different forms, such as inner joins, outer joins (left, right, full), and cross joins, each serving a specific purpose based on how the data should be associated. For example, an inner join retrieves records that have matching values in both tables, while a left join returns all records from the left table and the matched records from the right table.

Normalizing, indexing, and aggregations serve different functions in a database. Normalizing refers to the process of organizing data to minimize redundancy, which does not directly bring data together but instead optimizes its structure. Indexing helps improve the speed of data retrieval, enhancing performance but not inherently linking tables. Aggregations, on the other hand, summarize and compute data from one table rather than combining rows from multiple tables.

Thus, the process of bringing together data stored in different tables is