A geodatabase is a collection of geographic datasets of various types.
The information below will help provide a foundation for learning about and effectively using geodatabases for your GIS work.
Fundamental datasets in the geodatabase
One geodatabase concept is the dataset. It is the primary mechanism for organizing and using geographic information in ArcGIS. The geodatabase contains the following primary dataset types:
- Feature class
- Raster dataset
- Table
Creating a collection of these dataset types is the first step in designing and building a geodatabase. You will typically start by building a number of these fundamental dataset types. You'll then add to or extend your geodatabases with more advanced capabilities (such as by adding topologies, networks, or subtypes) to model GIS behavior, maintain data integrity, and work with a set of spatial relationships.
Geodatabase storage in tables and files
Geodatabase storage includes both the schema and rule base for each geographic dataset, as well as tabular storage of the spatial and attribute data. All three primary datasets in the geodatabase listed above, as well as other geodatabase elements, are stored using tables. The spatial representations in geographic datasets are stored as either vector features or rasters. These geometries are stored and managed in fields along with traditional attributes.
A feature class is stored as a table. Each row represents one feature. In the polygon feature class table in the image below, the Shape field contains the polygon geometry for each feature. The Polygon value is used to specify that the field contains the coordinates and geometry that define one polygon in each row.
One geodatabase strategy is to use a database management system (DBMS) to scale GIS datasets to extremely large sizes and numbers of users, for example, to support small databases for one or a few users up to instances with hundreds of millions of features and thousands of simultaneous users. Tables provide the primary storage mechanism for geographic datasets. Structured Query Language (SQL) queries and processes rows in tables, and the geodatabase strategy is designed to use these capabilities.
Advanced geographic datasets extend feature classes, rasters, and attribute tables
Various geodatabase elements are used to extend tables, features, and rasters to model spatial relationships, add behavior, improve data integrity, and extend the geodatabase's capabilities for data management.
The geodatabase schema includes the definitions, integrity rules, and behavior for each of these extended capabilities. These include properties for coordinate systems, coordinate resolution, feature classes, topologies, networks, relationships, and domains. This schema information persists in a collection of geodatabase meta tables in the DBMS. These tables define the integrity and behavior of the geographic information.
Geodatabase elements
As a GIS user, you'll work with the three fundamental dataset types listed above and shown below regardless of the system you use. You'll have a set of feature classes, a number of attribute tables, and most of the time, a large set of imagery and raster datasets to work with.
Fundamentally, all geodatabases contain this same kind of content. This collection of datasets can be thought of as the universal starting point for a GIS database design.
You can extend your data models to support certain essential capabilities as necessary. The geodatabase has additional data elements and dataset types that can be used to extend this fundamental collection of datasets.
See Extending tables, Extend feature classes, and Imagery and remote sensing in ArcGIS for more information.
Geodatabase transactions and versioning
Enterprise geodatabases use capabilities in the underlying DBMS to provide versions that offer scalable support for multiuser editing on large databases. With versioning, each editor can work in their own personal version of the geodatabase, make edits without impacting other editors or the production database, and incorporate their changes back into the system upon completion of their work. This transaction framework accommodates a variety of data management strategies suitable for individual users, teams of people, all the way up to international organizations and full web GIS deployments.
See Data management and transactions for more information.