With rising costs and uncertain economic conditions, organizations are turning to document databases and advanced data modeling techniques to enhance efficiency and reduce expenses. Document databases, such as MongoDB, offer significant cost savings by reducing development time with cross-language SDKs and flexible architectures, and by lowering operational costs through reduced hardware requirements for transaction throughput. These databases maintain familiar object-oriented programming models, eliminating the need for complex object-relational mapping (ORM) systems and allowing for more straightforward coding and data retrieval processes. In performance tests, document databases like MongoDB Atlas demonstrated a significant increase in transaction throughput and reduced operational costs compared to traditional relational databases, with MongoDB Atlas managing 50% more transactions per second on similar infrastructure. The tests also showed that MongoDB could achieve high transaction processing rates with lower infrastructure costs, making document databases an attractive option for organizations looking to optimize their database performance and reduce costs.