# Overview R-trees... #flashcard - Work with flexible, overlapping rectangles to divide space. This allows for an approach that can adapt to the data. This allows R-tree to efficiently handle both points and larger shapes in the same index structure. - The trade-off for this flexibility is that overlapping rectangles sometimes force us to search multiple branches of the tree. Modern R-tree implementations use sophisticated algorithms to balance this overlap against tree depth, optimizing for how databases actually read data from disk. This balance of flexibility and disk efficiency is why R-trees have become the standard choice for production spatial indexes. <!--ID: 1751507776879--> ![[2025-04-17_R-trees Index-1.png]] # Key Considerations # Pros # Cons # Use Cases - Geospatial searches, this is what is used in [[PostGIS]] # Related Topics