Built from the ground up with the single goal of providing fast web services for geospatial big data.
The MariaDB Geospatial data model extends the database’s native geospatial capabilities to provide support for ingesting and managing large collections of geospatial data.
Because the data model is an integral part of the platform, it was designed from the beginning to support web services, not just to be a repository of data. Every aspect of its architecture is influenced by this guiding ethic.
When we built the platform, we first thought of the “big data” problems in GIS, particularly big imagery, which has traditionally been a difficult problem for the incumbent technologies to solve. MariaDB Geospatial handles big imagery with ease, without just throwing hardware at the problem. It can easily build and manage mosaics made up of hundreds of thousands of source images, using very modest computational resources.
MariaDB Geospatial was designed to be compatible with cloud database architectures like MariaDB SkySQL, so it scales with your business. SkySQL makes it easy to set up, operate and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups. It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need.
Unlike most other solutions, MariaDB Geospatial does not need to extensively reorganize or load your data into the database. Data sources like large aerial imagery archives are loaded by reference, from where they already exist in your network-attached or cloud storage. Indexes, image overviews and map tile pyramids are created and managed in the database. Data integrity is always maintained. A modification or deletion of a source file is detected the next time it is accessed, and everything in the database is updated accordingly. An automatic internal registry keeps track of exactly which map tiles, etc. are affected by any update.
This architecture makes updates and maintenance a breeze. It keeps the size of the database quite small, while allowing the amount of actual data managed to grow enormously. Data volume is no longer a limiting factor. Collections can scale to petabytes with little to no loss of performance or maintainability.