Effective biodiversity conservation requires access to harmonized, high-resolution data across multiple spatial and institutional levels. However, data fragmentation and technical heterogeneity often limit the usability of locally collected datasets for regional or global decision-making. In this paper, we present a multi-level database harmonization approach that offers a flexible solution between isolated local databases and fully centralized systems. Our method enables the dynamic integration of diverse data sources into an SQL database by layering SQL queries on top of each other. Besides continuous data connections, it guarantees minimal load on data sources and minimal friction, harmonized outputs on a user-driven basis.We present this approach in a Hungarian case study on butterfly data, which uses field observation data from local, regional, and national monitoring programs collected by national park staff, citizen science initiatives, and global data repositories such as GBIF. The resulting umbrella database supports various outputs—from data tables and maps to policy-relevant analyses—while preserving institutional autonomy and enabling efficient data access via the OpenBioMaps framework. Our experience suggests that such a model can enhance the availability, visibility, and utility of biodiversity data and foster stronger links between data collectors, researchers, and conservation decision-makers.