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Geospatial Management.

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Import your data in open formats and track every version, without running your own tile server

Same map.Two different feeling.

THE OLD WAY

browser

1 request per tile

tile server fleet

find the file

object storage357,913,941 files

re-cut · re-upload · invalidate

a data change costs a day

THE GC WAY

browser

at most 2byte-range requests

no tile server

straight to storage, via C

object storage1 × basemap.pmtiles

a data change costs one upload

FILES NEEDED TO SERVE THE SAME 50 GB BASEMAP

357,913,9411

  1. 01

    The traditional way turns every square of the map into its own file. A typical map services needs hundreds of millions of them, each one a separate request, each one sitting behind a tile server you have to build and keep alive.

  2. 02

    The GC way packs the whole thing into one file on ordinary storage. The browser reads it directly. A data change costs one upload, not a day of re-cutting and redeploying.

How we manage Geospatial data?

3 steps. Files in, live map out.

01 IMPORT

GeoPackage
Shapefile · KML
GeoParquet
GeoJSON · NDJSON

… plus FlatGeobuf, MapInfo TAB,a zip, or just a URL

type &validate

schema

02 GENERATE

one click →.pmtilesevery zoom level

lands on object storage —nothing to deploy

publish

03 SERVE

OGC API Features (Part 1)
TileJSON
MapLibre Style JSON

copy-paste snippet

MapLibre · Leaflet · OpenLayers · cURL

Export back out in six open formats at any time — the data never gets trapped.

Import your data as-is. One click turns it into a single map archive, every zoom level included, served straight through open standards, ready for any client to read. Everything running underneath exists to make these three steps boring and repeatable, every time.

Supported Formats

  • GeoPackage
  • Shapefile
  • KML
  • GeoParquet
  • GeoJSON
  • NDJSON
  • FlatGeobuf
  • MapInfo

OGC Standard & Compatible

  • OGC API Features
  • TileJSON
  • MapLibre Style JSON

Datastore Integration

  • PostGIS
  • BigQuery
  • Snowflake
  • Earth Engine
  • Zarr
  • GeoParquet

Built to Scale

~90%scaling efficiencyacross distributed nodes.

Tested on national-scale location data and archives of tens of thousands of satellite images. Proven at the same scale government and enterprise systems run at.

Deployed your way

Available as a licensed deployment on your own private cloud or on-premise infrastructure, for organizations with data residency requirements.

  1. On-premise
  2. Private cloud

Request a demo to see it work with your data.

Request Demo