Database Design Checklist for Laravel Backend Systems

A beautiful web user interface is completely useless if the database behind it is structured poorly. In custom application development, a poorly designed database is a form of technical debt that accumulates interest at an alarming rate. Code can be refactored easily. Restructuring a production database with millions of active customer records is a high-risk, expensive operation that often leads to downtime.

In Laravel, Eloquent makes interacting with the database so simple that developers often forget about the database itself. They write migrations and define relationships without thinking about what is actually happening in MySQL or PostgreSQL. This guide is a database design manifesto for Laravel applications, focusing on five core principles of relational integrity and performance.

Principle 1: Store Currency as Integers (The Rule of Immutable Financial Math)

The Bad Pattern: Storing monetary values using a database FLOAT or DOUBLE column type. In migrations, it looks like $table->float('price');.

Floating-point numbers are designed for scientific calculations where approximate values are acceptable, but they are a disaster for financial data. Computers represent floating-point numbers as binary approximations. As you perform additions, subtractions, and multiplications, tiny rounding errors accumulate. Over thousands of transactions, $10.00 can slowly morph into $9.99999998, leading to accounting errors that are extremely difficult to locate and fix.

The Good Pattern: Store all monetary values as integers representing the lowest currency unit (e.g., cents, pence, paise). Store $10.50 as 1050 in an integer column ($table->integer('price_in_cents');). Store ¥500 directly as 500. When performing calculations—such as applying a tax percentage or a discount—do the math in integers using rounding rules. When displaying the price to the user, divide the integer by 100. This eliminates floating-point rounding errors entirely and guarantees consistent financial records.

Principle 2: Selective Recovery (The Hidden Costs of Soft Deletes)

The Bad Pattern: Applying Laravel's SoftDeletes trait to every database table by default. The thinking is: "Just in case a user or admin deletes something by mistake, we can restore it."

While soft deletes are incredibly useful for critical entities like users or orders, they carry hidden performance and structural costs. When you soft-delete a record, it remains in the table. Every index on that table continues to store the record. Every single database query must append a hidden WHERE deleted_at IS NULL clause. As the table grows, this increases the size of your indexes and degrades query performance. More importantly, soft deletes make unique database constraints difficult to manage. If a user deletes an account, and then tries to register again with the same email, a database-level unique constraint on the email column will throw an error because the soft-deleted user still exists.

The Good Pattern: Only use soft deletes on high-value, top-level business resources where compliance or operational history requires retention. For transaction logs, cart items, notification logs, and user preferences, use hard deletes. If data safety is a concern for secondary tables, handle it through proper daily database backups rather than polluting your active schema with soft-deleted rows.

Principle 3: Hybrid Modeling (JSON Columns vs. Relational Normalization)

The Bad Pattern: Creating a separate database table for every single minor attribute or set of key-value pairs. For example, creating a user_preferences table with rows for theme, notifications_enabled, and items_per_page, requiring a database JOIN statement every time a user logs in.

Conversely, the other bad pattern is storing highly structured relational data (like order items) inside a single JSON column on the orders table, making it impossible to query or index which products are selling best.

The Good Pattern: Use JSON columns selectively for unstructured, client-specific settings that the database engine doesn't need to query or aggregate. User preferences are the perfect use case. You can define a JSON column in migrations: $table->json('settings');. In Laravel, you cast this to an array or object in the Eloquent model. The data is stored cleanly inside the users table, requiring no joins. However, if the business needs to search, sort, or aggregate data (e.g., finding all users who have notifications enabled), that attribute belongs in its own normalized, indexed database column.

Principle 4: Referential Fast-Paths (Indexing All Foreign Keys)

The Bad Pattern: Defining foreign key relationships in migrations without creating indexes. In migrations, a developer writes $table->foreignId('user_id'); but forgets to declare it as an index.

Every time you load a user's orders, Laravel runs a query like SELECT * FROM orders WHERE user_id = 5. If the user_id column in the orders table is not indexed, the database must scan every order record in the database to find the ones matching ID 5. When the database is small, this is fast. When you have 500,000 orders, the query takes seconds and blocks other operations.

The Good Pattern: Every single foreign key column must be indexed. Laravel makes this simple. Use the helper method in migrations: $table->foreignId('user_id')->index(); or $table->foreignId('user_id')->constrained()->index();. This ensures that parent-child database lookups take less than a millisecond, even on massive datasets.

Principle 5: Database-Level Integrity Checks

The Bad Pattern: Relying entirely on Laravel application-level validation to protect data integrity. For example, verifying a unique email only in the Laravel form request, while leaving the database column as a generic text column without a unique constraint.

Validation can be bypassed. If two users submit the registration form at the exact same millisecond, both validation requests can pass simultaneously, resulting in duplicate records in the database. If an API request is made directly, or a background script runs, invalid data can bypass your forms completely.

The Good Pattern: Treat the database as the ultimate guardian of truth. Use database-level constraints for all critical business rules: unique() for unique columns, nullable(false) to prevent empty values, and foreign key constraints to prevent orphan records. If the application logic makes a mistake, the database constraint acts as the final line of defense, throwing an exception and preventing data corruption.

Normalizing the Foundation

A well-normalized database is a prerequisite for a fast, maintainable codebase. It reduces redundancy, guarantees consistency, and ensures that query tuning is a simple task. When building software, spend the necessary time planning your schema before writing your Laravel migrations.

If you are planning a database architecture for a complex business platform or need to resolve performance issues on an existing database schema, visit my backend API development services page to see how I help client teams design stable systems.