In today's fast-paced digital landscape, embedded databases are becoming increasingly popular as they enhance the functionality of applications without requiring significant modifications. Neo4j, a graph database, can be used as an embedded database to provide added value and functionality to applications. This approach enables organizations to minimize their investment in product development while shortening the product life cycle by embedding someone else's technology into their products. Graph databases are designed to capture and store relationships between data, providing powerful features that wouldn't be possible without them. The rapid growth of the graph database market is driven by its ability to uncover hidden insights through graph analytics, improving machine learning feature engineering, and providing more explainable AI. Factors fueling graph adoption include speed, AI maturity, ease of use, cost, standardization, and knowledge graphs that expose metadata and business rules, enabling data scientists to quickly identify and use the data they need while preserving context. By embedding a graph database in a product, organizations can take advantage of these benefits without straying from their core competency.