Database Consistency: Beyond the Basics

This article delves into the challenges of maintaining database transactional consistency in high-concurrency environments. Using a Spring Boot example, the author demonstrates how default pagination and idempotency checks can lead to data inconsistencies (missing rows or duplicate updates) when processing a large volume of sales data. The article thoroughly explains database isolation levels (READ UNCOMMITED, READ COMMITED, REPEATABLE READ, SERIALIZABLE) and optimistic/pessimistic locking strategies. Ultimately, by employing the REPEATABLE READ isolation level and optimistic locking, the author effectively resolves data inconsistencies and significantly improves performance.