Example Concept: Database optimization for scalability often involves trade-offs between query performance and data consistency. For instance, adding indexes can speed up read operations but may slow down writes due to the overhead of maintaining the index. Similarly, denormalizing data can improve read performance by reducing the need for joins, but it may lead to data redundancy and increased storage costs. Partitioning data can enhance scalability by distributing load across multiple servers, but it may complicate query logic and data retrieval.