Cloud-based infrastructures enable applications to collect and analyze massive amounts of data. NoSQL databases endowed with high availability and excellent scalability through their easy deployment on cloud-computing platforms, become a more attractive data-storage solution for these big-data applications. Unfortunately, to date, there is little methodological support for software development on these platforms. In this work, we focus on applications that collect spatial data over time, since, due to the pervasiveness of mobile application clients, this class of applications is among the most popular applications today. To support the development and maintenance of these applications, this thesis develops a set of general guidelines for the design of HBase storage, taking advantage of the special 3D structure of HBase and a specific three-dimensional "schema'' for geospatial applications. These guidelines and schemas have been evaluated with multiple data sets as well as through the migration of an existing geospatial application to the cloud.