Database contention occurs when multiple processes try to access the same data simultaneously, leading to processing delays and potential errors. This issue is particularly relevant for applications that have reached significant scale. To avoid contention issues, it's essential to understand isolation levels and ACID transactions, which ensure data integrity in a database. Common examples of contention include multiple transactions trying to update the same row or table at the same time. Diagnosing contention can be challenging but involves checking performance metrics, error messages, and querying internal tables. To resolve contention issues, consider using random index key values, breaking up large transactions into smaller ones, and increasing data normalization.