concept
A spatial database is a database dedicated to storing and managing geospatial data. Geospatial data includes maps, satellite images, meteorological data, remote sensing data, etc. These data are usually related to geographic location, spatial relationship and earth coordinate system.
Spatial databases can store and manage a large amount of geospatial data, and provide efficient data query and analysis functions. It can help users mark locations on the map, search for places, measure distances, calculate areas, draw paths, and more.
Common spatial database software includes Oracle Spatial, PostGIS, Microsoft SQL Server Spatial, etc. These software have different functions and performance characteristics, and users can choose the most suitable software according to their needs.
Commonly used spatial data models include vector models and raster models. The vector model adopts the description method of geometric objects, and abstracts geospatial objects into basic geometric elements such as points, lines, and planes for storage and processing. The grid model adopts the description method of pixels, and divides the geospatial objects into grids composed of pixels for storage and processing. The spatial index structure is used to accelerate the query and retrieval of spatial data. Commonly used spatial index structures include R-tree, Quadtree, KD-tree, etc. R-tree is a multidimensional index structure used to organize spatial data and improve query efficiency. R-tree adopts the structure of B-tree, recursively divides the spatial object into multiple rectangular blocks, and builds a tree structure. Each node contains a rectangle representing the area covered by its children. The root node represents the entire space, while the leaf nodes contain the actual space objects. The R-tree storage structure is shown in the figure below:
R-tree is a multidimensional index structure used to organize and manage spatial data. R-tree adopts the structure of B-tree, recursively divides the spatial object into multiple rectangular blocks, and builds a tree structure. Each node contains a rectangle representing the area covered by its children. The root node represents the entire space, while the leaf nodes contain the actual space objects.
The difference between spatial database and ordinary database
The main difference between a spatial database and an ordinary database is that it can store and process spatial data. Compared with ordinary databases, spatial databases provide more spatial data types and functions, which can be more convenient for storage, query and analysis of spatial data.
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Spatial databases provide a variety of spatial data types, such as points, lines, surfaces, polygons, etc., which can directly store and manipulate spatial data. Ordinary databases only support basic data types, such as integers, strings, etc., and cannot directly store and manipulate spatial data.
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Spatial database adopts special spatial index structure, such as R-tree, Quadtree, etc., which can optimize the query and retrieval of spatial data. Ordinary databases only support B-tree indexes, which cannot well support the query and retrieval of spatial data.
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Spatial database provides a wealth of spatial analysis functions, such as buffer analysis, overlay analysis, distance calculation, etc., which can facilitate the processing and analysis of spatial data. The MySQL common database does not support the spatial analysis function.
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Spatial databases can handle large-scale spatial data, such as satellite remote sensing data, global terrain data, etc. However, MySQL ordinary databases will have performance problems when processing large-scale data.
mainstream spatial database
- Oracle Spatial: a spatial database developed by Oracle, which supports vector and raster-based spatial data storage and management, and provides efficient spatial query and analysis functions.
- PostGIS: The spatial extension of PostgreSQL supports vector-based spatial data storage and management, and provides a wealth of spatial query and analysis functions and operations.
- Microsoft SQL Server Spatial: The spatial extension of Microsoft SQL Server supports vector-based spatial data storage and management, and provides efficient spatial query and analysis functions.
- MySQL Spatial: The spatial extension of MySQL supports vector-based spatial data storage and management, and provides basic spatial query and analysis functions.
- GeoServer: Java-based spatial data publishing and management platform, supports multiple data formats and spatial databases, and can publish spatial data as standard map services and Web services.
- GeoTools: A Java-based GIS toolkit that supports multiple spatial databases and data formats, and provides rich spatial query and analysis functions.