In this article authors provide outline and formal description of visual techniques that support analysis and extraction of patterns from information encoded in spatial graphs. Both known methods (such as transparency, magnification, etc.) are being presented and offered by the authors for the enhanced analysis (such as projective shadows, illumination distance, gradient stenciling, etc.). The goal of this research is to assist in graph data visualization and mining tasks by providing a set of supplementary techniques for effective information comprehension and analysis. Components of computer graphics framework required for each type of technique (for example – support of shaders, presence of stencil and depth buffers, etc.) are being listed. The result of this analysis is presented in tabular form, comparing fitness of identified techniques against different three-dimensional graph layout algorithms, semantic data domains and desired analysis processes. This allows to identify main requirements for computer graphics framework being used for data visualization as a part of particular graph visualization software system technical specification. Conclusion about achieved results is made. Information about potential future researches in this field is presented.