Welcome to our QGIS tutorial! In this post, we will explore how to work with spatial databases in QGIS, a powerful open-source Geographic Information System (GIS) application. Spatial databases allow you to store, manage, and analyze spatial data efficiently. We will cover the basics of connecting to a spatial database, performing queries, and visualizing the spatial data in QGIS.
What is a Spatial Database?
A spatial database is a database that is optimized to store and query spatial data, which includes information about the location and shape of geographic features. Common spatial databases include PostgreSQL with PostGIS, MySQL with spatial extensions, and SQLite with SpatiaLite. These databases allow for advanced spatial queries and analysis, making them ideal for GIS applications. We can turn a traditional relational database into a powerful spatial database.
List of Spatial Databases
Here’s a list of popular spatial databases that are widely used for storing, managing, and querying spatial data:
- PostgreSQL with PostGIS
- An open-source relational database that extends PostgreSQL to support geographic objects, allowing for advanced spatial queries and analysis.
- MySQL with Spatial Extensions
- MySQL supports spatial data types and functions, enabling basic spatial operations and indexing.
- SQLite with SpatiaLite
- A lightweight database that extends SQLite with spatial capabilities, making it suitable for mobile and embedded applications.
- Oracle Spatial and Graph
- A feature of Oracle Database that provides advanced spatial data management and analysis capabilities, including support for complex spatial data types.
- Microsoft SQL Server with Spatial Data Types
- SQL Server includes built-in support for spatial data types and functions, allowing for the storage and querying of geographic data.
- MongoDB with GeoJSON
- A NoSQL database that supports geospatial queries using GeoJSON format, suitable for applications requiring flexible data models.
- Cassandra with GeoCassandra
- An extension of Apache Cassandra that adds support for geospatial data, allowing for distributed storage and querying of spatial information.
- IBM Db2 with Spatial Extender
- A relational database that includes spatial capabilities for managing and analyzing geographic data.
- Couchbase with Geospatial Indexing
- A NoSQL database that provides geospatial indexing and querying capabilities for location-based applications.
- Redis with RedisGeo
- An in-memory data structure store that supports geospatial indexing and querying, suitable for high-performance applications.
These spatial databases vary in terms of features, performance, and use cases, so the best choice depends on your specific requirements and the nature of your spatial data.
How to Connect QGIS to Spatial Database
PostGIS
PostGIS is the best spatial database to be paired with QGIS. QGIS seems can utilize all the features that PostGIS has to offer. We can create new features (line, polygon, points) directly from QGIS to PostGIS. We can also save the QGIS project into PostGIS.
Read our previous article on how to connect QGIS to PostGIS for a step by step guide.
SQL Server
Microsoft SQL Server is one of the best relational database system out there. It supports spatial data storage out of the box. If you want to build your own SQL Server spatial database, you can follow the tutorial below:
Conclusion
There are many spatial databases options you can choose for your GIS project. PostGIS and SQL Server are the most widely used and most compatible among GIS software. If the price is crucial for you, PostGIS could be the best solution you can get.