Graph data, also known as graph databases, have revolutionized the way we deal with complex data systems. The history of graph databases dates back to the 1970s when E.F. Codd developed the concept of relational databases, which led to the emergence of tabular databases that were later found to be limited in their ability to handle complex data models. In the 1990s, new data technologies like NoSQL emerged, but they had limitations such as denormalization and lack of expressiveness. Graph databases, on the other hand, offer a more expressive data model that allows for the storage and retrieval of graph-based relationships between entities. Today, graph database technology meets or exceeds ambitions, leading to a new era of innovation in data systems. The future of graph data holds promise with advancements in areas like eventual consistency, reliability, and scalability, as well as the development of new technologies such as peer-to-peer clusters and domain-specific partitioning. As ambition grows, so does the potential for innovation in graph databases, making them an exciting area to explore.