High-level query languages promise more expressive and concise queries than traditional SQL yet remain primarily theoretical due to limited real-world tooling. In this paper, we present an API such as the HIFUN high-level query language that integrates with relational databases for real-time data operations and supports NoSQL backend for schema management and data visualization. By leveraging graph-based schema models, our approach enables developers to issue high-level functional queries that the API transparently rewrites into optimized SQL statements. We describe the system architecture, detail the transformation pipeline from relational schema to graph representations and discuss how we incorporate hybrid SQL–NoSQL strategies. We also review related literature on multi-model queries, domain-specific languages (DSLs), and federated query systems. Results from experimental use cases highlight the viability of bridging HIFUN’s expressive power with real-world developer workflows .