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?
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.
In SQL Server, foreign keys are essential for maintaining referential integrity between tables. When setting up a foreign key, we have various options for handling actions when the referenced data is deleted. One of these options is ON DELETE SET DEFAULT.
This feature can be particularly useful in scenarios where it’s important to maintain the relationship while ensuring that the foreign key column doesn’t end up with invalid or null values.
When creating a foreign key constraint in SQL Server, we have the option of including ON DELETE SET NULL in the definition. When we use this option in a foreign key, it tells SQL Server to automatically set the foreign key column values to NULL in the child table when the corresponding primary key record in the parent table is deleted.
When using aggregation functions in PostgreSQL, we have the option of including a FILTER clause. This clause allows us to narrow down – or filter – the rows that are fed to the aggregate function.
This can be be a handy way to provide functionality that we might otherwise need to use a CASE statement or perhaps a CTE.
In this article, we’ll take a look at PostgreSQL’s FILTER clause, and see how it can simplify our SQL queries by replacing CASE statements with more concise code.
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.
One of the various options we have when creating or rebuilding indexes in SQL Server is specifying a fillfactor. If we create or rebuild an index without specifying a fillfactor, then the default fillfactor is applied.
In some cases, using the default fillfactor may be fine, even ideal. In other cases it could be less than ideal, even terrible.
Let’s look at what fillfactor is, how it works, and how we can use it to enhance database performance.
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.
WHILE loops are a powerful feature in most programming languages that allow developers to execute a block of code repeatedly as long as a specified condition is true. However, there are times when we may need to exit a loop prematurely based on certain criteria. SQL Server caters for this possibility with the BREAK keyword.
In this article, we’ll explore how to effectively use the BREAK keyword within WHILE loops in SQL Server.
There are around a dozen types of index in SQL Server, but the most commonly used index type would have to be the clustered index. By default, a clustered index is automatically created when we create a primary key, and so if your tables have primary keys, then there’s a pretty good chance you’ve got clustered indexes all over your database.
But what exactly is a clustered index?
Let’s delve into what a clustered index is, how it works, its relationship with primary keys, and why it’s so important for our database performance.