The big data GIS system which includes the storage and management of spatial big data, spatial analysis, stream data processing and visualization technology, dedicates to provide a comprehensive support for big data GIS infrastructure software and services, thus to make more users easily manage spatial big data "gold mine".

Meanwhile, traditional GIS is reconstructed based on IT big data technology, which supports the distributed storage, processing and analysis of massive classical spatial data, and achieves the performance improvement of order of magnitude.


Provide Multiple Distributed spatial Data Engines
  • Support HBase and HDFS engines for large scale vector / raster data.
  • Provides distributed spatial file engine DSF which has high performance and full quantity computing capacities.
  • Supports files of GeoJSON, GeoCSV, etc. on HDFS.
  • Support Elasticsearch engines for stream data.
  • Support MongoDB engine for 2D map vector / grid tiles and 3D tiles.

Provide Multiple Spatial Data Analysis
  • Kernel level extended Spark spatial data model.
  • Supports 5 categories covering 20 kinds of spatial big data analysis.
  • Supports distributed computing of classic spatial analysis for 4 categories covering 15 kinds of vector data.
  • Supports distributed computing of classic spatial analysis for 6 categories covering 23 kinds of raster data.

Provides flexible secondary development capabilities for Spark distributed environments
  • Supports Java, Scala and Python.
  • Supports data query methods of Spark SQL and DataFrames.
  • The extensibility of spatial data storage engine users.

Vector/raster data provides highperformance distributed dynamic rendering technology

Providing Plentiful and Cool Spatial Visualization of Big Data.