R-trees in Data Structure

Here we will see the R-Trees data structure. The R-Trees are used to store special data indexes in an efficient manner. This structure is very useful to hold special data queries and storages. This R-trees has some real life applications. These are like below −

  • Indexing multidimensional information

  • Handling game data

  • Hold geospatial coordinates

  • Implementation of virtual maps

One example of R-Tree is like below.

Corresponding R-tree is like below −

Properties of R-Trees

  • R-Trees are made of with single root, internal and leaf nodes

  • The root has a pointer to the largest region in the special domain

  • The parent nodes will hold child nodes where child nodes completely overlap the region of parent nodes

  • Leaf nodes hold data about MBR to the current object

  • MBR-Minimum bounding region is the minimum boundary box parameter surrounding the region under consideration

Difference between Quad-trees

Quad TreeR-Tree
Tiling level optimization is requiredR-Tree do not require any optimization
Quad-tree can be formed on B-treeR-tree does not follow the structure of B-tree
Spatial Index creation is fasterSpatial Index creation is slower
Nearest neighbor querying is slower, but the Window querying is faster.Nearest neighbor querying is faster, but the Window querying is slower.