The evolution of graph databases and graph-based systems has been a significant area of growth in the technology sector, with Neo4j remaining at the forefront. The development of a common graph query language, GQL, is underway to standardize this emerging industry standard. Graph technology's maturity and simplicity, particularly the property graph data model, have contributed to its widespread adoption across various industries. Initially developed for content management, graph databases have proven versatile and can be applied to dynamic systems with large amounts of data. Intelligent applications leveraging static and dynamic information are becoming increasingly common, making graphs an ideal representation of real-world structures. The integration of graph technology in artificial intelligence (AI) and machine learning (ML) is also evident, as most models in these disciplines rely on graph-based representations.