Geoscientific array data, such as satellite imagery, geoscientific model, and weather prediction model data, are a significant subset of scientific array data that use geolocation information as index. The sharp growth in the availability of such data demands new data management infrastructures. The traditional relational DBs has problems managing such spatial-array-oriented data due to the limitations of relational algebra(RA) and SQL. In this paper, we investigate this problem and summarize the basic requirements for big geoscientific array data management. Following the requirements, we propose a novel data model in which the geoscientific arrays are modeled as spatial array objects supported by a two-level spatial index. Based on the data model, we implement GeoMix, a geoscientific database system inside IBM Informix, aiming to provide middleware-level support for data management on geoscientific array data. It provides users with a SQL insert/select interface as well as a set of APIs enabling direct data access by native arrays. Last, we show, by a series of experimentations, the power of GeoMix to provide middleware-level support for complex analytics on real satellite imagery and model data. © 2013 ACM.