When designing a relational database, four key principles should be followed. First, correctly use primary and foreign key constraints to ensure data integrity and association accuracy; second, perform standardized design reasonably, usually reaching the third normal form (3NF), eliminating redundancy and ensuring data consistency; third, establishing appropriate indexes for common queries to improve query performance but avoid over-index; finally, using consistent naming specifications and structural styles to enhance readability and maintainability. Mastering these principles can help build a clear, efficient and robust database structure.

When designing a relational database, the focus is on clear structure, consistent data, and efficient query. As a SQL developer, mastering several key design principles can help you avoid many detours.

1. Use primary and foreign key constraints correctly

The primary key is the unique identifier of each record in the table, while the foreign key is the key link connecting multiple tables. Ignoring the primary foreign key constraints will lead to data confusion and unreliable query results.

• The primary key should select unchanged, unique, and non-empty fields, such as self-increment ID or UUID.
• Foreign keys Make sure that the referenced fields are primary keys or unique indexes, otherwise invalid associations may result.
• Don't skip foreign key constraints to "save trouble". It can prevent dirty data from being inserted and help the database optimizer to do query optimization.

For example: In the order table, customer_id is pointed to the customer table as a foreign key. If this field has no foreign key constraints, you may insert a customer ID that does not exist at all, causing data errors.

2. Proper standardized design

Database standardization is the basis for eliminating redundancy and ensuring data consistency. It is enough to achieve the third normal (3NF) in general development.

Common practices include:

• Split the duplicate data into independent tables, such as not directly putting the user address information in the user table.
• Make sure each field depends on the primary key, not other non-primary key fields.
• Avoid storing multiple values in a field, such as the "tags" field splicing multiple tags with commas, which will destroy the first normal form.

Of course, sometimes moderate anti-normalization is also done for the sake of query efficiency, but it is clear that this is to exchange time with space or consistency.

3. Create an appropriate index for common queries

Indexing is an important means to improve query performance, but the more the better. The key is to understand your query pattern.

suggestion:

• Indexes are created by default on primary and foreign keys.
• Index fields that are often used for WHERE, JOIN, ORDER BY.
• Pay attention to the order of combined indexes, and the principle of leftmost prefix is very important.
• Regularly analyze slow query logs to see which fields are missing indexes.

For example, if you often log in according to the user's email address, add an index in the email field of the users table; if you often query orders by order time and user ID, you can create a combined index (user_id, order_date).

4. Use consistent naming norms and structural styles

Good naming specifications can make team collaboration smoother and facilitate post-maintenance.

It is recommended to adopt a unified style, such as:

• Table names are all lowercase, and words are separated by underscores, such as orders and order_items.
• The primary key uses id, and the foreign key uses [associated table name]_id, such as user_id.
• Field naming clearly expresses the meaning and avoids abbreviation ambiguity, such as not using "status" instead of "status".
• All tables use the InnoDB engine (transaction-supported) and the character set is unified to utf8mb4.

These details look small, but can provide great convenience during long-term maintenance.

Basically that's it. Designing a database is not complicated, but details are easily overlooked. Incorporating these principles into daily development allows you to write clearer and more robust SQL structures.

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