PolarDB:Overview

Core components

Geometry engine

The geometry engine provides storage and computing capabilities for vector data such as points, lines, planes, and volumes. It supports various geometry data formats such as SHP, GeoJSON, WKT, and WKB. The geometry engine is fully compatible with PostGIS functions and has definite advantages in spatial data caching, spatial indexing, and spatial parallel computing. It can improve the query and analysis performance of large-scale vector data by more than five times.

Raster engine

The raster engine provides storage and computing capabilities for remote sensing images, digital elevation models (DEMs), and grid data. It is compatible with multiple raster data source formats such as Tiff, HDF4, HDF5, GRIB, and NetCDF. The raster engine provides object-oriented storage capabilities, and supports OSS-based raster data lake scaling. A single row can store a large object of more than 1 TB. The raster engine also provides a variety of basic operators involving raster spatial relationship identification, raster pyramid, raster statistics, raster attributes, raster image processing, raster algebra, as well as business algorithms such as color balancing, mosaic, DEM algorithms, and D8 catchment algorithms. It has distinct advantages in large-scale raster data storage and computing scenarios.

Moving object engine

The moving object engine mainly provides data storage and computing capabilities for moving objects such as people, vehicles, ships, and aircraft. The moving object engine provides native storage, indexing, and segmentation optimization for 4D trajectories (2D or 3D and time). It can add custom attributes to each trajectory point, define spatio-temporal events, efficiently compress and resample tens of billions of trajectory points, and support various native spatio-temporal operators, such as trajectory segmentation, trajectory stay points, trajectory similarity, and spatio-temporal relationship identification.

GeomGrid engine

The GeomGrid engine mainly provides spatial grid construction and the grid coding and query capabilities for 2D and 3D spatial objects. The GeomGrid engine supports multiple meshing rules (such as GeoSOT and H3), spatial object encoding, object and code query operations, aggregation and analysis capabilities based on spatial grids, and grid degeneration capabilities.

Surface model engine

The surface model engine provides the storage and computing capabilities for semantic 3D data expressed in surface meshes. The surface model engine can process building information modeling (BIM) data, deconstruct and structure models based on semantics, support complex 3D spatial analysis and large-scale federated retrieval, provide model simplification algorithms, and interface with mainstream front-end 3D rendering engines.

Volume model engine

The volume model engine mainly provides the storage and computing capabilities for anisotropic data characterized by non-homogeneous volume meshes. The volume model engine can process complex geological volume data, support grid truncation at sequence boundaries, support business interpolation algorithms, support complex spatial analysis and large-scale federated retrieval, provide model simplification algorithms, and interface with mainstream front-end 3D rendering engines.

Scene model engine

The scene model engine mainly provides the storage and computing capabilities for refined rendering models. The scene model engine can import models in multiple formats, such as OSGB, glTF/GLB, and OBJ, support algorithms such as space clipping and merging, texture clipping and simplification, provide model simplification algorithms, and interface with mainstream front-end 3D rendering engines. It also supports accurate analysis on visibility and shadow ratios.

Point cloud engine

The point cloud engine mainly provides the storage and computing capabilities for massive point cloud data collected by LADAR systems. The point cloud engine supports block spatial indexing in databases, point cloud compression loss, point cloud spatial query and calculation, point cloud thinning and simplification, and can be connected to mainstream front-end 3D rendering engines.

Path engine

The path engine mainly provides the storage and computing capabilities for topological graph data expressed in points and edges (such as pipe networks and road networks). The path engine can build network topologies based on point and edge models, and support multiple pathfinding algorithms such as TSP, K-shortest, turn restriction, and bidirectional Dijkstra's.

Quick display engine

The quick display engine supports quick rendering of spatial data in GanosBase. For vector and raster data, the quick display engine performs hierarchical aggregation based on spatial characteristics. It uses visibility culling algorithms to build fast display indexes without pre-tiling to support rendering, and local updates of the indexes are supported. For various types of 3D data, the fast display engine constructs rendering levels for 3D models by using model simplification, texture compression, and data stitching, and dynamically generates a display format that the rendering engine can recognize. The quick display engine changes the traditional display mode of pre-tiling and provides integrated visualization and computing capabilities to ensure data verisimilitude.

Unified management

Various types of spatio-temporal multi-modal data

GanosBase supports different data types (such as geometry, raster, trajectory, and geographic grid), storage structures, and function capabilities. GanosBase can replace the traditional technical framework that involves multiple data types and multiple storage methods. It provides unified management on various spatio-temporal data types, reducing business complexity and O&M costs.

Compliance with OpenGIS standards and full compatibility with the PostGIS syntax

GanosBase supports the transparent migration of existing PostGIS geometry applications, supports 2D, 3D, and 4D coordinate spaces, allows you to create 2D and n-D spatial indexes, and supports planar and spherical computing. You can control the spatial computing accuracy. Compared with PostGIS, GanosBase improves the performance by more than five times in various common spatio-temporal query scenarios.

Powerful, flexible, simple, and specialized management of grid data

GanosBase can import multiple types of raster data, such as HDF4, HDF5, GRIB, and NC. It supports transparent query processing based on OSS. It can manage large raster objects with a single row of more than 1 TB and improve the performance by more than 10 times in parallel operation mode. It supports a variety of basic raster operators and business algorithms such as image mosaic, clipping, color balancing, and DEM processing.

Integrated storage, computing, and rendering of 3D data

GanosBase can import common 3D model data types, such as IFC (BIM), GLFT, GLB, OBJ, OSGB, and 3D geological models. After data is imported, it can perform complex 3D analysis and 3D queries, and its quick display engine can provide rendering capabilities without pre-tiling. GanosBase improves the computing efficiency of 3D data by more than 50 times than traditional solutions.

Diversified geographic meshing, coding, and aggregation capabilities

GanosBase supports multiple meshing rules such as GeoSOT and H3. It can quickly code hundreds of millions of 2D and 3D spatial objects based on grids, perform real-time aggregation queries based on grid codes, and interface with the MVT fast display technology to implement efficient rendering of aggregation attributes.

Trajectory management and visualization of a large number of moving objects

GanosBase implements trajectory management for various moving objects, such as people, vehicles, ships, and aircraft, in up to four-dimensions. GanosBase supports complex computing of trajectories, events, and polymorphic attributes, such as complex storage, compression, segmentation, similarity judgment, and stationary point judgment. Compared with the traditional point model, the native trajectory model improves the performance by nearly 50 to 100 times in spatio-temporal analysis scenarios.

Polymorphic tiered storage of spatial data

GanosBase provides polymorphic tiered storage of spatial data in PolarDB for PostgreSQL (Compatible with Oracle). The database service not only supports Elastic Block Storage, but also allows you to store data in Object Storage Service (OSS). You can store partitions in a partitioned table on OSS, or store spatio-temporal large columns in the table on OSS. You can also perform create, read, update, delete, and index operations on such data stored on OSS. The multi-level cache ensures performance and is fully transparent to customers. Polymorphic tiered storage can greatly reduce storage costs and ensure data operations.