Modern applications require intelligence and learning to support smart decision-making in real time. They must be able to scale without limits, meet unexpected demand, and provide straightforward security and flexible architecture. Graph databases are emerging as a solution for intelligent applications, offering a flexible and scalable foundation for connection-oriented applications. They use nodes and relationships to store data, enabling queries that can run in fractions of a second, and support both graph transactions and graph analytics. Graph data science unlocks insights from connected data, providing algorithms such as pathfinding, centrality, community detection, heuristic link prediction, and similarity. These technologies are crucial for building intelligent applications that meet the evolving requirements of modern software development.