CC BY 4.0Räder, AndreasAndreasRäder2025-05-192025-05-192023-04-30https://doi.org/10.24406/publica-4679https://publica.fraunhofer.de/handle/publica/48767710.24406/publica-4679Looking at the underlying technologies of modern and sustainable web applications, which rely on well-defined structured data, databases capable of handling knowledge graphs play a crucial role. RDF stores, also known as triple stores, serve as backbones of such systems, enabling the storage and access of standardized, highly structured linked data via query engines and APIs. Moreover, the need for coexistence with property graph databases is becoming increasingly important, particularly for the efficient federated processing of large graph datasets. Achieving both data and query interoperability remains a major challenge in current research, as the data models and query languages differ significantly in several key aspects. There are also ongoing developments integrating traditionally used relational database systems as intrinsic parts of existing infrastructure. PostgreSQL, as a widely used open-source solution, offers great flexibility in terms of extensibility and adaptability. The most recent releases of the PostgreSQL extension Apache AGE elevate this database engine into an integrated system that functions as a graph-enhanced, hybrid relational database. Like typical graph databases, AGE uses the Property Graph model and includes a query engine compliant with the openCypher guidelines. In combination with PostgREST, this relational system can be directly transformed into a RESTful API. This work explores the feasibility of converting an extended PostgreSQL stack into a triplestore, thereby addressing the challenges of interoperability between RDF and Property Graph stores.enKnowledge GraphsRDFProperty GraphsSPARQLCypher000 Informatik, Informationswissenschaft, allgemeine Werke000 Informatik, Informationswissenschaft, allgemeine Werke::000 Informatik, Wissen, Systemeseminar paper