Today a huge amount of geospatial data is being created, collected and used more than ever before. The ever increasing observations and measurements of geo-sensor networks, satellite imageries, point clouds from laser scanning, geospatial data of Location Based Services (LBS) and location-based social networks has become a serious challenge for data management and analysis systems. Traditionally, Relational Database Management Systems (RDBMS) were used to manage and to some extent analyse the geospatial data. Nowadays these systems can be used in many scenarios but there are some situations when using these systems may not provide the required efficiency and effectiveness. In these situations, NoSQL solutions can provide the efficiency necessary for applications using geospatial data. It is important to differentiate between the physical way a NoSQL product is implemented, and the interfaces, coding and access methods they use for the abstraction of data. This paper provides an overview of the major types of NoSQL solutions, their advantages and disadvantages and the challenges they present in managing geospatial data. Then the paper elaborates on serving geospatial data using standard geospatial web services with a NoSQL database as a backend.