Spatial database

A spatial database is a special kind of database that has been made better to include spatial data. This means it can work with information about objects in a geometric space, like where things are and how they are shaped. It has tools to ask questions about this spatial data and to analyze it.

Most spatial databases can show simple shapes such as points, lines, and polygons. Some can even handle more complicated shapes like 3D objects, topological coverages, and triangulated irregular networks. Regular databases are good at handling numbers and words, but they need extra features to work well with spatial data.

A geographic database is a type of spatial database that stores and works with geographic data, which is information linked to places on Earth. This is very useful for geographic information systems (GIS). Today, most database systems have added special features for spatial data, and some GIS companies have made their own additions too.

The Open Geospatial Consortium created the Simple Features specification to help make sure databases can handle spatial data in a standard way. There is also a standard called SQL/MM Spatial that adds spatial features to the structured query language.

Characteristics

A spatial database is a special kind of database that can store and work with maps and shapes. It adds new types of data that let it hold points, lines, and areas, which are ways to show real-world objects like cities, roads, and parks.

These databases also let people ask special questions using regular database language. For example, you can find out how far two places are from each other, see if one area overlaps another, or create new shapes by changing existing ones. This helps in many map-related tasks.

Spatial index

A spatial index helps a spatial database work faster when looking for places or objects. Normal databases use simple lists to find things, but this doesn’t work well for maps or 3D spaces. So spatial databases use special kinds of indexes made just for places.

Some common ways to make a spatial index include:

Binary space partitioning (BSP-Tree)
Bounding volume hierarchy (BVH)
Geohash
Grid (spatial index)
HHCode
Hilbert R-tree
k-d tree
m-tree
Octree
PH-tree
Quadtree
R-tree – often the best way to organize spatial data. It groups objects by their minimum bounding rectangle (MBR).
R+ tree
R* tree
UB-tree
X-tree
Z-order (curve)

Spatial query

A spatial query is a special kind of search that spatial databases can do. These databases can handle maps and shapes, like points, lines, and areas. The queries are different from regular database searches because they look at how these shapes relate to each other.

Different databases use different names for their search tools. For example, PostGIS, a free tool that adds map features to PostgreSQL, has many useful functions. Some of these include checking the distance between points, seeing if shapes touch or overlap, and finding the size or center of a shape. These tools help answer questions like which cities are inside which countries.