Exploring property graphs with SQL/PGQ in PostgreSQL

Using relational databases, how do you efficiently determine an optimal path covering all your tickets in the game of Ticket to Ride? Traditionally, solutions to graph-like problems in PostgreSQL—such as reachability and shortest-path discovery—have relied on Recursive Common Table Expressions (CTEs), which are often verbose, difficult to optimize, and complex to maintain. The SQL:2023 standard introduces SQL/PGQ (Property Graph Queries), finally allowing a relational database like PostgreSQL to treat graph traversals as first-class, declarative operations. And we are working to bring SQL/PGQ support to a future release of PostgreSQL, hopefully in PostgreSQL 19!

In this session, you will explore property graph (SQL/PGQ) capabilities using the Ticket to Ride—like schema as a practical example. You will learn important aspects of SQL/PGQ: from defining a Property Graph over standard relational tables to using MATCH clause to implement pathfinding logic.

Beyond the game, the session provides an under the hood look at the SQL/PGQ implementation in Postgres. The transformation of graph patterns into relational join trees and the complexities of path-variable bindings will be discussed. You will leave with a clear understanding of the Postgres implementation of the SQL/PGQ standard from one of the authors of the patch himself.