Content
The Debate That Never Ends
Should price calculations happen in a stored procedure or in your API layer? Should data validation fire in a database trigger or in your application code?
The Case for Business Logic in SQL
Data Integrity Is Guaranteed
When logic lives in the database, it enforces rules regardless of which application writes data.
Performance for Set-Based Operations
SQL is purpose-built for operating on sets of rows. Aggregation queries are faster than fetching rows and summing in a loop.
Example: Price Calculation in SQL
The Case for Application Code
Testability and Maintainability
Unit testing a Python function is straightforward. Testing a stored procedure requires a running database.
Example: Price Calculation in TypeScript
When to Use What
SQL-Side Logic For:
Reporting and analytics queries
Data integrity constraints
Audit logging via triggers
Bulk data transformations
Application Code For:
Complex workflows with external calls
Rules that change frequently
Cross-service logic
Anything that needs unit tests
Rapid Prototyping with AI2SQL
AI2SQL makes prototyping business logic as SQL fast. Describe your rule in plain English and get working SQL to verify it produces the right results before deciding where it belongs.
Decision Framework
Does it need to be enforced regardless of caller? Database constraint
Is it a read-only aggregation? SQL query or view
Does it involve external systems? Application code
Will it change frequently? Application code
Is it a bulk transformation? SQL


