Explore why database cardinality is a crucial concept within database design and management. Learn how to define cardinality and when to use different types of cardinality design.
Cardinality in databases describes the relationship between two entities and is a fundamental aspect of database design that affects how information is stored, accessed, and maintained. By understanding cardinality, you can build your knowledge on effectively designing database systems suitable for the data types you work with. In this article, you can explore cardinality, why it is necessary, common types, and typical examples of how you might see cardinality chosen across professional industries for different purposes.
Cardinality describes how tables in a database relate to each other. Your database's cardinality tells you if a value in one table links to just one or several values in a different table. This relationship can vary widely, from exclusive pairings to a vast network of connections.
High cardinality means a column in a table has many unique values. For example, if you were dealing with a table that records every book published, the ISBN column would have high cardinality because each book has a unique ISBN. High cardinality columns have high levels of unique information, making them useful for searches and indexing.
On the other hand, low cardinality means a column has many repeated values. An example of this would be if your table included book genres rather than ISBNs. Since you can assign a finite number of genres, the variety of values is limited, making the table low cardinality. Low cardinality fields are easier to manage and can speed up certain queries but offer less granularity.
While cardinality and ordinality are terms that come up in the context of databases, each has a unique purpose and conveys different types of information. Cardinality focuses on the uniqueness and relationship between data in different tables, essentially telling us how many connections exist between data sets. Ordinality describes the order of elements within a data set. While cardinality maps the landscape of data relationships, ordinality tells us about the sequence or position of data points within that landscape.
Cardinality focuses on the types of relationships, which include one-to-one, one-to-many, and many-to-many, indicating how many instances of an entity relate to another. Modality, on the other hand, indicates whether or not a relationship is required between entities.
For instance, modality can specify whether every learner must enroll in at least one course or if it’s optional for a learner to enroll in any course. If every learner must enroll, the modality is “one,” while if the relationship is optional, the modality is “zero.”
Cardinality is key to how well databases work, particularly when it comes to finding and storing information efficiently. Cardinality determines how data points link and organize within the database, impacting everything from how quickly you can retrieve the data to how accurately it’s stored.
For businesses that depend on fast access to data, properly setting up cardinality can lead to faster searches, more efficient data storage, and higher accuracy of the information held. This means better service for customers and smoother operations. Cardinality helps organize data, ensuring you can quickly find what you’re looking for, correctly place new information, and record data with appropriate granularity.
When modeling data, you can choose three main types of cardinality: one-to-one, one-to-many, and many-to-many. You’ll make this choice depending on the type of data you have, the relationships you are interested in, and the requirements of your field.
One-to-one (1:1) relationships link each value of a table to a singular value in another table. This type of relationship is less common than other types of cardinality, and you’ll typically find it used to add specific information to an entity's ID. For example, a database for employee management might have an “Employees” table and an “Employee Details” table, where each employee links to exactly one set of details, and each set of details connects precisely to one employee.
One-to-many (1:N) relationships are among those you’ll frequently encounter in database design. This design occurs when a singular value in a table connects with multiple values in another table. For instance, in a library database, a single author can write multiple books, but only one author writes each book. This relationship allows for the efficient organization and retrieval of related records across tables.
Many-to-many (M:N) relationships happen when several values in one table link to multiple values in another table. This type of relationship typically requires a third table to break down into two one-to-many relationships. For example, in a zoo database, an “animal” table and a “food” table might have a many-to-many relationship, as each animal can eat several types of food, and each type can feed several animals. The join table could be a “Feeding schedule” table, tracking which animals eat which food, effectively managing the many-to-many relationship.
Cardinality is applied across industries in any sector that manages data and relationships between data. Understanding cardinality helps structure data according to the natural relationships within the information being managed. For example, you might find cardinality types chosen for specific applications, such as:
E-commerce platforms: In an e-commerce database, the relationship between customers and orders is typically one-to-many, as a single customer can place multiple orders over time. This understanding helps design the database to manage customer data and their order histories efficiently.
Health care systems: Patient and appointment databases in health care systems may use one-to-one relationships for security. For example, a specific medical record might relate to one patient identifier, ensuring privacy and data integrity.
Educational institutions: Schools and universities can use databases where relationships between courses, students, and professors are many-to-many. Students can enroll in several courses with multiple professors, professors can teach several courses with many students, and each course can have multiple students and professors associated with it.
Inventory management: In inventory management systems, the relationship between products and suppliers might be one-to-many if a supplier provides various products, but each product comes from a single supplier.
You can continue learning about database management with tailored courses on the Coursera learning platform. As a beginner, you would benefit from the Database Structures and Management with MySQL course by Meta, which guides you through introductory topics on designing relational database systems efficiently and effectively.
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