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How do you compare and contrast different ERD models, such as Chen, Barker, or UML?

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Entity-relationship diagrams (ERDs) are graphical tools for designing and documenting the structure and relationships of data in a relational database management system (RDBMS). However, there are different ERD models that use different notations, symbols, and conventions to represent the same concepts. In this article, you will learn how to compare and contrast three common ERD models: Chen, Barker, and UML.

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Mark Davis

1 Chen model

The Chen model, named after its creator Peter Chen, is one of the oldest and most widely used ERD models. It uses rectangles to represent entities, diamonds to represent relationships, and ovals to represent attributes. It also uses cardinality and participation symbols to indicate the degree and optionality of the relationships. For example, a one-to-many relationship between a customer and an order is shown as a single line with a crow's foot on the order side, and a double line to indicate that every order must have a customer.

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Mark Davis
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I started with the Chen style many years ago. It works well, and is analogous to Barker style. The thing I don't like about Chen is the diamond for the relationship name. First, the diamonds clutter the diagram. Second, the diamonds are often too small for the names I choose.

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2 Barker model

The Barker model, developed by Richard Barker, is another popular ERD model that is based on the natural language approach. It uses boxes to represent entities, lines to represent relationships, and labels to indicate the role and cardinality of each entity in the relationship. It also uses different types of lines and symbols to show the optionality and exclusivity of the relationships. For example, a one-to-many relationship between a customer and an order is shown as a solid line with a slash on the customer side, and a dashed line with a circle on the order side, indicating that a customer can have zero or more orders, and an order must have one and only one customer.

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Mark Davis
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I use the Barker style as my go-to for all data modeling. It's expressive, uncluttered, simple (but not too simple), and easy to read. I've used Chen and UML in the past, but I find Barker more effective and usable overall.

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3 UML model

The UML model, or the Unified Modeling Language model, is a general-purpose modeling language that can be used for various types of systems, including databases. It uses classes to represent entities, associations to represent relationships, and properties to represent attributes. It also uses multiplicity and role names to indicate the cardinality and role of each entity in the relationship. For example, a one-to-many relationship between a customer and an order is shown as a line with a 1 on the customer side, and a * on the order side, and the role names customer and order above the line.

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Mark Davis
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I have used UML extensively for software design, and it's still the best thing going in that space. And I was one of the first architects (no brag) to create data models using the class diagramming constructs in UML. And it's just not worth the trouble. UML is far too expressive and not nearly as readable when compared to other data modeling methods. Plus, most modeling tools assume that when you choose UML as the modeling style, that you want to use ALL the features that pertain to software and systems, and they drag all that stuff into your data model. Ugh.

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4 Comparison criteria

To compare and contrast different ERD models, you can use some criteria such as the readability, expressiveness, standardization, and compatibility of each model. Readability refers to how easy it is to understand the meaning and logic of the diagram. Expressiveness refers to how well the model can capture the complexity and diversity of the data and the relationships. Standardization refers to how consistent and widely accepted the model is among different users and tools. Compatibility refers to how well the model can be translated or converted to other models or formats.

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Mark Davis
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Barker is simple, readable, standardized, and well supported in any data modeling tool. It takes less than five minutes to educate a non-technical person to read a Barker ERD. Chen is simple and readable, but the fussy diamonds for relationship names severely limit the number of characters you can use when naming relationships. In my experience, Chen isn't well supported in modeling tools. UML is far too complicated, and somehow still not as readable, when compared to Chen and Barker. It's certainly standardized, and there is decent tool support out there, but every UML tool I've used will drag in every model type and diagram element when all you want to do is model some data.

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5 Strengths and weaknesses

Each ERD model has its own strengths and weaknesses depending on the criteria and the context. For example, the Chen model is highly expressive and standardized, but it can also be verbose and cluttered. The Barker model is simple and readable, but it can also be ambiguous and limited. The UML model is versatile and compatible, but it can also be complex and confusing. Therefore, you should choose the model that best suits your needs and preferences, and be aware of the trade-offs and implications of each model.

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6 Best practices

No matter which ERD model you use, there are some best practices that can help you create effective and accurate diagrams. Ensure that you use meaningful and consistent names for entities, relationships, and attributes. Additionally, make sure to use appropriate data types and constraints for attributes, as well as avoid redundant or unnecessary entities, relationships, or attributes. Subtypes and supertypes should be used to represent hierarchical or categorical relationships, while associative entities should be used to represent many-to-many relationships. Normalization techniques can also be employed to reduce data anomalies and improve data integrity. Finally, validate and verify your diagram with stakeholders and experts.

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7 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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How do you compare and contrast different ERD models, such as Chen, Barker, or UML?

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1 Chen model

2 Barker model

3 UML model

4 Comparison criteria

5 Strengths and weaknesses

6 Best practices

7 Here’s what else to consider

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