In relational databases, a foreign key is typically a field that is linked to another table‘s primary key field in a relationship between two tables.
However, there’s also a type of foreign key we call the self-referencing foreign key. The self-referencing foreign key refers to a field within the same table, creating a relationship between rows in the same table.
In SQL databases, triggers can play a significant role in automating responses to specific events within a database. Whether we’re dealing with data validation, logging changes, or enforcing business rules, SQL triggers can be a handy tool to ensure that certain actions are taken automatically when certain conditions are met.
This article covers what SQL triggers are, how they work, and provides an example to illustrate their use.
In relational database design, the concept of a “key” is fundamental. Keys are essential for uniquely identifying records in a table, ensuring data integrity, and facilitating efficient data retrieval. Among the different types of keys used in SQL, the natural key is one that often sparks discussion among database designers, especially when compared with the surrogate key.
Let’s explore the concept of a natural key, its advantages and disadvantages, and look at a practical example to illustrate its use.
While the primary key is almost certainly the most discussed key in SQL, there are other types of keys that we shouldn’t forget. One such key is the alternate key.
In this article, we’ll look at the concept of the alternate key in SQL.
There are many different “key” types in SQL. We have the primary key, the foreign key, and even the unique key.
But have you heard about the candidate key?
One of the core principles that ensure data integrity in relational database management systems (RDBMSs) is atomicity. When dealing with SQL, understanding what “atomicity” and “atomic” means can help you design more reliable and robust databases.
Atomicity is a key concept that underpins how SQL transactions operate, ensuring that either all steps in a transaction are completed successfully, or none are. This article looks at the meaning of atomic in SQL, its importance, and how it fits into the broader context of database management.
Domain integrity is an important concept in relational database management that ensures the accuracy, validity, and consistency of data within a database. It refers to the enforcement of rules and constraints that ensure data entered into a database adheres to a predefined set of acceptable values. This helps maintain the quality of data and prevents the entry of erroneous, incomplete, or invalid data into the system.
When working with relational databases, data accuracy and consistency are paramount. When we talk about maintaining the integrity of the data within a relational database, several types of integrity come into play. One of the most fundamental is entity integrity.
This concept is crucial for ensuring that each record within a database table is uniquely identifiable, which in turn supports the reliability of the data. In this article, we will look into what entity integrity is, why it matters, and how it is implemented in practice. We’ll also look at an example to clarify the concept further.
In SQL (and computer science in general), a Boolean expression is a logical statement that evaluates to either true or false. Some RDBMSs provide a boolean data type that can store values that are either true or false (or unknown). PostgreSQL is one such RDBMS.
In PostgreSQL, the Boolean type is called boolean and it uses 1 byte.
When looking at ways to fix slow running SQL queries, one of the first things we might do is look at what indexes are available to support the query. If none are available, then we might look at creating one. And if there is an index, perhaps it doesn’t cater for the query as well as it could.
Indexes are often created on a single column, but this isn’t the only way to create an index. We can also create indexes on multiple columns. These are typically known as composite indexes.