Data Modeling for Scalable FinTech Applications

# Data Modeling for Scalable FinTech Applications

Financial Technology architectures do not have the luxury of "eventual consistency." If money is moving between systems, the database must absolutely obey the rules of ACID (Atomicity, Consistency, Isolation, Durability).

The Double-Entry Ledger Pattern

Never store a user's absolute "balance" as a simple, updatable integer column in a User table.

Instead, build an immutable transactions ledger. When a user deposits $50, you append a row: amount: +50. When they spend $10, you append amount: -10. A user's total balance is inherently generated dynamically by querying SUM(amount).

If absolute speed is required for a UI layer, cache the aggregated sum locally via Redis, but the true source of truth relies permanently on the mathematically unbreakable ledger trail.

## Soft Deletes

In FinTech systems, never run DELETE statements. Everything must rely on "soft deletes" (e.g., flipping an is_active boolean to false) to maintain flawless compliance and audit histories for regulatory bodies.