What are the different types of relationships in entity-relationship modeling?

Entity-relationship modeling (ERM) is a technique for designing and representing data structures and their connections in a clear and logical way. It is widely used in software design, especially for relational databases, to define the entities, attributes, and relationships that make up the data model. In this article, we will explore the different types of relationships in ERM and how they are depicted using symbols and notation.

1 One-to-one relationships

A one-to-one relationship occurs when each entity in one set is associated with exactly one entity in another set. For example, a person can have only one passport, and a passport can belong to only one person. A one-to-one relationship is represented by a single line connecting the two entity sets, with a crow's foot at each end to indicate the mandatory participation of both entities.

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Yves Mulkers

I turn Data Pains into Business Gains | Host of Data Strategy Guru's Podcast | Thought Leadership & Brand Awareness | Data Strategist at 7wData | Speaker & Mentor
In ERM, a one-to-one relationship is like a lock and key in security—unique pairings ensuring data integrity. It's a strategic cornerstone, reflecting precision and exclusivity in database design. For leaders, it's a reminder: meticulous matches in data architecture are as crucial as in security systems, underpinning robust, tailored data management. Precision in ERM safeguards data integrity.
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2 One-to-many relationships

A one-to-many relationship occurs when each entity in one set is associated with zero or more entities in another set, but each entity in the second set is associated with at most one entity in the first set. For example, a customer can place many orders, but each order can be placed by only one customer. A one-to-many relationship is represented by a single line connecting the two entity sets, with a crow's foot at the end of the entity set that can have multiple occurrences, and an optional circle at the other end to indicate the optional participation of the entity set that can have zero occurrences.

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Yves Mulkers

I turn Data Pains into Business Gains | Host of Data Strategy Guru's Podcast | Thought Leadership & Brand Awareness | Data Strategist at 7wData | Speaker & Mentor
In ERM, one-to-many relationships link a singular entity to several others, akin to a tree's trunk supporting multiple branches. This structure is ideal for clear hierarchies and straightforward data retrieval when one entity, like a customer, is central to many dependent entities, such as orders. However, it's not without drawbacks. If overused or poorly managed, it can lead to inefficient database performance and complex joins that slow down data retrieval. Careful indexing and query optimization are essential. Employ this relationship when there's a clear dominant entity, but steer clear for many-to-many interactions that require more flexible, interconnected structures. Opt for one-to-many in clear hierarchies.
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3 Many-to-many relationships

A many-to-many relationship occurs when each entity in one set is associated with zero or more entities in another set, and each entity in the second set is associated with zero or more entities in the first set. For example, a student can enroll in many courses, and a course can have many students. A many-to-many relationship is represented by a single line connecting the two entity sets, with a crow's foot at both ends to indicate the multiple occurrences of both entities. However, many-to-many relationships are usually resolved into two one-to-many relationships by introducing an associative entity that represents the association between the two original entity sets. For example, an enrollment entity can link a student entity and a course entity, and store additional attributes such as the grade or the date of enrollment.

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Yves Mulkers

I turn Data Pains into Business Gains | Host of Data Strategy Guru's Podcast | Thought Leadership & Brand Awareness | Data Strategist at 7wData | Speaker & Mentor
Many-to-many relationships in ERM are like social networks: individuals (entities) form connections (relationships) that can't be mapped in pairs. Instead, think of a network node, like a Facebook group, linking many users with many interests, illustrating the interconnected nature of modern data. Interconnected data mirrors life's network.
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4 Recursive relationships

A recursive relationship occurs when an entity set is associated with itself, meaning that an entity can have a relationship with another entity of the same type. For example, an employee can be a manager of another employee, or a product can be a component of another product. A recursive relationship is represented by a single line connecting the entity set to itself, with a crow's foot at one end to indicate the multiple occurrences of the entity, and a role name or a cardinality ratio to specify the nature and degree of the relationship.

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Yves Mulkers

I turn Data Pains into Business Gains | Host of Data Strategy Guru's Podcast | Thought Leadership & Brand Awareness | Data Strategist at 7wData | Speaker & Mentor
In ERM, recursive relationships are like mirrors reflecting back on the entity itself, such as an employee who both manages and is managed. They're a double-edged sword—vital for mapping complex hierarchies yet tricky, potentially tangling data if not meticulously defined. Best used with a dash of caution, they're perfect for charting organizational trees, provided you're clear on the roles to avoid a data labyrinth. Hierarchies demand meticulous mapping.
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5 Subtype relationships

A subtype relationship occurs when an entity set is divided into smaller subsets based on some distinguishing characteristics or attributes. For example, an employee entity can be subdivided into manager, engineer, and accountant entities, each with their own specific attributes and relationships. A subtype relationship is represented by a double line connecting the supertype entity to the subtype entities, with a triangle symbol indicating the type of inheritance or specialization. The subtype entities can have either total or partial participation, and either disjoint or overlapping categories, depending on the constraints and rules of the data model.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Molly Hickey

Technical Product Leader - B2B SaaS, APIs, Identity and Access Management
The relationships can also be mandatory or optional. For example, a mandatory relationship describing a database holding information about people dictates every person **must** have 1 home address for the model to be accurate (they have to live somewhere). This is a 1 to 1 relationships between the person and home address. Optional relationships means that the data for the related object isn’t always there and is not mandatory for the model to be accurate. For example, a person may have a landline phone or could have multiple (if it was still 1993), but they may have no landline phones. Therefore, the relationship between the person and the landline phone number is an **optional** 1:many relationship.
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What are the different types of relationships in entity-relationship modeling?

1

2

3

4

5

6

1 One-to-one relationships

2 One-to-many relationships

3 Many-to-many relationships

4 Recursive relationships

5 Subtype relationships

6 Here’s what else to consider

Software Design

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What are the different types of relationships in entity-relationship modeling?

1

2

3

4

5

6

1 One-to-one relationships

2 One-to-many relationships

3 Many-to-many relationships

4 Recursive relationships

5 Subtype relationships

6 Here’s what else to consider

Software Design

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