We address the problem of performing spatial queries on tetrahedral meshes. These latter arise in several application domains including 3D GIS, scientific visualization, finite element analysis. We have defined and implemented a family of spatial indexes, that we call tetrahedral trees. Tetrahedral trees subdivide a cubic domain containing the mesh in an octree or 3D kd-tree fashion, with three different subdivision criteria. Here, we present and compare such indexes, their memory usage, and spatial queries on them.