Graph Databases for Travel: How Martin Tuncaydin Maps Routes, Hubs, and Connections

Graph Databases for Travel: How Maps Routes, Hubs and Connections Over two decades working at the intersection of travel technology and data architecture, I've watched the industry wrestle with a fundamental challenge: how do you model the intricate web of connections that make modern travel possible? Traditional relational databases force us to flatten what is inherently a network problem—flights connecting airports, trains linking stations, buses bridging cities, all woven together into a tapestry of possible journeys. The answer, I've found, lies in graph databases. Not as a trendy alternative to SQL, but as the natural data structure for representing how the world actually moves. Why Travel Data Belongs in a Graph When I first encountered graph databases in the early 2010s, I was skeptical. Another NoSQL movement promising to solve everything? But as I began modeling multi-modal journey planning scenarios, something clicked. The relationship between London Heathrow and Paris Charle