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Comparison

Best cloud geospatial analytics platforms compared

Wherobots is the cloud geospatial analytics platform for raster and vector data, built as the AI Context Engine for Physical World Data. See how it compares with Snowflake, Databricks and BigQuery.

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Raster and vector in one query

Zonal statistics in spatial SQL.

Serverless or in your VPC

Distributed on Apache Spark.

Built for AI agents

Wherobots MCP (Model Context Protocol) Server for AI tools.

Cloud data platforms

Wherobots, Snowflake, Databricks and BigQuery side by side

Each row is a capability a geospatial team tests before it picks a platform. Every answer for Snowflake, Databricks and BigQuery comes from that vendor’s own documentation, linked below the table. For every Wherobots capability and spatial SQL function, see the Wherobots vs. Apache Sedona feature comparison.

Wherobots, Snowflake, Databricks and BigQuery side by side
Capability Spatial compute Wherobots Cloud Fully managed spatial compute, RasterFlow, Havasu catalog, and Spatial AI tools. Data warehouse Snowflake Cloud data warehouse with geospatial types. Lakehouse Databricks Lakehouse with native spatial SQL. Data warehouse Google BigQuery Serverless warehouse with geography functions.
Raster and vector analysis
Vector data Geometry and geography types and spatial SQL functions Included: GEOMETRY and GEOGRAPHY types, 389 spatial SQL functions for vector and raster Included: GEOGRAPHY and GEOMETRY types, ST_ and H3 functions Included: GEOMETRY (generally available, GA) and GEOGRAPHY (Public Preview), 97 ST_ functions Included: GEOGRAPHY type on the WGS84 spheroid
Raster data A raster type or raster functions in SQL Included: Out-of-database raster, loading pixels on demand from object storage or a SpatioTemporal Asset Catalog (STAC) Not included: Not documented Not included: Not documented Partial: Earth Engine images and Cloud Optimized GeoTIFFs through ST_REGIONSTATS
Raster and vector in one query Statistics of raster pixels inside vector polygons Included: RS_ZonalStats and RS_ZonalStatsAll in spatial SQL Not included: Not documented Not included: Not documented Included: ST_REGIONSTATS (GA)
Imagery inference Computer vision models run over satellite and aerial imagery Included: RasterFlow (Public Preview), with five built-in models plus your own PyTorch or TensorFlow model Partial: AI_COMPLETE on image files; no geospatial imagery documented Not included: Not documented Partial: ML.ANNOTATE_IMAGE with Cloud Vision; no geospatial imagery documented
Scale and operations
Scale Distributed and serverless, on Apache Spark Distributed virtual warehouses Distributed on Apache Spark and Photon Distributed and serverless
How compute runs Serverless in Wherobots Cloud, or deployed in your VPC Managed warehouses you size Serverless, Pro or Classic SQL warehouses Serverless, with optional slot reservations
SQL and Python Included: Spatial SQL, Python and Scala Included: SQL and Snowpark Python Included: SQL and PySpark Included: SQL and BigQuery DataFrames
Pricing model Spatial Units per hour; RasterFlow by data processed Credits per warehouse size and hour Databricks Units (DBUs) Per TiB scanned, or capacity per slot-hour
Open formats and AI access
GeoParquet Read and write Included: Read and write Not included: Not documented Not included: Not documented Included: Load and export
Apache Iceberg geometry types Geometry columns in Iceberg tables Included: Iceberg geometry and geography types with a declared coordinate reference system (CRS) Included: GEOGRAPHY and GEOMETRY columns in Iceberg tables Included: GEOMETRY and GEOGRAPHY columns in Iceberg v3 tables Not included: GEOGRAPHY not supported in BigQuery Iceberg tables
MCP server for AI agents An official Model Context Protocol server Included: Wherobots MCP Server for Claude, Cursor, and VS Code Copilot Included: Snowflake-managed MCP server (GA) Included: Genie One MCP (GA) and Databricks SQL MCP (Beta) Included: BigQuery remote MCP server (GA)

Sources, checked October 2026: Wherobots Cloud from the Wherobots vs. Apache Sedona feature comparison and Wherobots documentation; Snowflake geospatial data types, AI_COMPLETE, Iceberg data types and MCP server; Databricks ST geospatial functions, SQL warehouse types, Iceberg v3 and MCP services; BigQuery raster data, geospatial data, Iceberg tables, ML.ANNOTATE_IMAGE, MCP server and pricing. “Not documented” means the vendor’s documentation does not describe the capability.

Libraries and databases you run yourself

Wherobots, ArcGIS GeoAnalytics Engine and PostGIS side by side

The same rows for two tools teams often weigh against a spatial compute platform. Neither is a managed analytics service. GeoAnalytics Engine runs on a Spark cluster you run. PostGIS runs on your own PostgreSQL server or on hosted PostgreSQL such as Amazon RDS. Each answer comes from the vendor’s or project’s own documentation, linked below the table.

Wherobots, ArcGIS GeoAnalytics Engine and PostGIS side by side
Capability Spatial compute Wherobots Cloud Fully managed spatial compute, RasterFlow, Havasu catalog, and Spatial AI tools. Spark library ArcGIS GeoAnalytics Engine Esri spatial analysis on your own Spark clusters. Database extension PostGIS Open-source spatial extension for PostgreSQL.
Raster and vector analysis
Vector data Geometry types and spatial SQL functions Included: GEOMETRY and GEOGRAPHY types, 389 spatial SQL functions for vector and raster Included: 148 ST_ SQL functions plus analysis tools Included: geometry and geography types
Raster data A raster type or raster functions in SQL Included: Out-of-database raster, loading pixels on demand from object storage or STAC Included: Raster type with 30+ raster functions and tools since version 2.0 Included: raster type in the postgis_raster extension
Raster and vector in one query Statistics of raster pixels inside vector polygons Included: RS_ZonalStats and RS_ZonalStatsAll in spatial SQL Included: RT_ZonalStatistics Included: ST_SummaryStats over ST_Clip
Imagery inference Computer vision models run over satellite and aerial imagery Included: RasterFlow (Public Preview), with five built-in models plus your own PyTorch or TensorFlow model Not included: Not documented Not included: Not documented
Scale and operations
Managed service Who runs the compute Included: Fully managed by Wherobots Not included: A library you install and license on a Spark cluster you run You run the database, or rent hosted PostgreSQL such as Amazon RDS and Cloud SQL
Scale Distributed and serverless, on Apache Spark Distributed on the Spark cluster you run One PostgreSQL server
How compute runs Serverless in Wherobots Cloud, or deployed in your VPC On Databricks, Amazon EMR, Azure Synapse or Google Cloud Managed Spark Self-run, or on managed PostgreSQL such as Amazon RDS and Cloud SQL
SQL and Python Included: Spatial SQL, Python and Scala Included: Spark SQL, Python and Scala Included: SQL; Python through drivers such as psycopg
Pricing model Spatial Units per hour; RasterFlow by data processed Prepaid subscription, connected (core-hours) or disconnected, plus your Spark compute Free (GPL v2 or later), plus your database server
Open formats and AI access
GeoParquet Read and write Included: Read and write Included: Read and write Not included: Not documented
Apache Iceberg geometry types Geometry columns in Iceberg tables Included: Iceberg geometry and geography types with a declared CRS Not included: Not documented Not included: Not documented
MCP server for AI agents An official Model Context Protocol server Included: Wherobots MCP Server for Claude, Cursor, and VS Code Copilot Not included: Not documented Not included: Not documented

Sources, checked October 2026: Wherobots Cloud from the Wherobots vs. Apache Sedona feature comparison and Wherobots documentation; ArcGIS GeoAnalytics Engine SQL functions, raster data, install, GeoParquet and licensing; PostGIS data management, ST_SummaryStats and license; Amazon RDS PostGIS. “Not documented” means the vendor’s or project’s documentation does not describe the capability.

Customer proof

We went from babysitting compute jobs for a week to getting results before lunch.

Steven Yee Founding Staff Engineer, Aarden.ai

Computer vision for geospatial data: RasterFlow

Bring your own data

Query a STAC catalog. Index your own Cloud Optimized GeoTIFFs (COGs) in a GDAL Raster Tile Index, a file that lists each image and its footprint. Then build a mosaic from them with build_gti_mosaics. RasterFlow reads from and writes to your own S3-compatible storage.

Bring your own rasters

Mosaicking

RasterFlow builds one seamless, analysis-ready mosaic across an area of interest and a time range. Built-in datasets cover Sentinel-2 with all 12 L2A bands at 10 m, and USDA NAIP aerial imagery at 30 cm and 60 cm, reprojected onto your output grid.

Build a Sentinel-2 mosaic

Cloud cover removal

Sentinel-2 mosaics skip scenes with 75% or more cloud cover. They mask cloud, cloud shadow and thin cirrus pixel by pixel from the Scene Classification Layer, then take the per-pixel median of the clear observations.

See the cloud filtering rules

Edge effect cleanup

Inference runs over overlapping patches. Patch size and clip size set the overlap, and a merge mode such as weighted average blends neighboring patches. Overlapping windows reduce the edge effects that non-overlapping tiles leave at seams.

See overlapping inference

Five built-in models

Meta SAM3 detects objects from a text prompt. Fields of the World maps field boundaries, Tile2Net maps sidewalks and crosswalks, Meta CHM v1 estimates canopy height, and ChesapeakeRSC maps rural roads. Change detection runs a model over two seasons or years in one pass.

Open the Model Hub

Bring your own model

Run your own PyTorch or TensorFlow model. Export a PyTorch model as a PyTorch 2 archive, load it from Amazon S3 or Hugging Face, and run it over any mosaic on GPU runtimes, alongside the built-in models.

Bring your own model

Standard formats after inference

Mosaics and predictions are written as Zarr stores. vectorize_mosaic converts predictions into polygons written as GeoParquet, and Build Multiscales adds overview levels for map viewing. WherobotsDB turns the vectors into PMTiles.

Visualize RasterFlow outputs

Open interoperability

RasterFlow reads COG, GeoParquet and Parquet, writes Zarr and GeoParquet, and reaches Apache Iceberg tables through a Managed Catalog. WherobotsDB joins the vectorized results with parcels, roads or assets in spatial SQL.

See supported formats

Serverless, priced before you run

No cluster to provision or manage. RasterFlow bills by data processed (pixels × bands × time periods × a complexity factor), so you can calculate a task’s cost before it runs. A 150,000 km² Sentinel-2 mosaic with all 12 bands costs about $13.50 in RasterFlow and about $50 to generate and export in Google Earth Engine.

Compare with Google Earth Engine

RasterFlow results in the platform you already run

Databricks

Wherobots reads and writes managed Iceberg tables in Databricks Unity Catalog and writes external Delta tables there. Field boundaries, roofs or canopy heights from RasterFlow land as Unity Catalog tables for Databricks ML models and BI dashboards.

Connect Unity Catalog

Snowflake

Wherobots writes Apache Iceberg tables to your own Amazon S3 bucket. Snowflake supports externally managed Iceberg tables with GEOMETRY and GEOGRAPHY columns, so RasterFlow output can be queried alongside your Snowflake data.

See Snowflake Iceberg types

Google BigQuery

RasterFlow writes vectorized results as GeoParquet, and BigQuery loads GeoParquet into GEOGRAPHY columns. Predictions then join your BigQuery tables in SQL.

Load GeoParquet into BigQuery

Function reference

Every spatial SQL function, by platform

Search 826 spatial SQL functions from each platform’s own function reference, filter by vector or raster, and see which platforms have each one. Functions match by name, so the same operation can appear under two names, such as ST_GeomFromWKT in Wherobots and ST_GEOGRAPHYFROMWKT in Snowflake. Raster functions also carry different prefixes on each platform (RS_ in Wherobots, RT_ in GeoAnalytics Engine, ST_ in PostGIS Raster).

Function Category Wherobots Cloud Snowflake Databricks BigQuery GeoAnalytics Engine PostGIS What it does
ST_Area Measurement Functions Available Available Available Available Available Available compute area
ST_AsBinary Geometry Output / Export Available Available alias of ST_ASWKB Available Available Available Available output WKB
ST_AsText Geometry Output / Export Available Available alias of ST_ASWKT Available Available Available Available output WKT
ST_Buffer Geometry Processing Available Available Available Available Available Available compute buffer geometry; Wherobots also supports spheroidal
ST_Centroid Geometry Processing Available Available Available Available Available Available return centroid point
ST_Contains Predicates / Topological Relationships Available Available Available Available Available Available test containment
ST_Difference Overlay Functions Available Available Available Available Available Available compute point-set difference
ST_Dimension Geometry Accessors Available Available Available Available Available Available return topological dimension (0=point, 1=line, 2=polygon)
ST_Disjoint Predicates / Topological Relationships Available Available Available Available Available Available test disjointness
ST_Distance Measurement Functions Available Available Available Available Available Available compute Euclidean distance
ST_EndPoint Geometry Accessors Available Available Available Available Available Available return last point of linestring
ST_Intersection Overlay Functions Available Available Available Available Available Available compute point-set intersection
ST_Intersects Predicates / Topological Relationships Available Available Available Available Available Available test intersection
ST_Length Measurement Functions Available Available Available Available Available Available return length/perimeter
ST_NumPoints Geometry Accessors Available Available alias of ST_NPOINTS Available Available Available Available return number of points
ST_PointN Geometry Accessors Available Available Available Available Available Available return Nth point from linestring
ST_StartPoint Geometry Accessors Available Available Available Available Available Available return first point of linestring
ST_Union Overlay Functions Available Available Available Available Available Available compute point-set union of two geometries
ST_Within Predicates / Topological Relationships Available Available Available Available Available Available test if A is within B
ST_X Geometry Accessors Available Available Available Available Available Available return X coordinate of point
ST_Y Geometry Accessors Available Available Available Available Available Available return Y coordinate of point
ST_AsGeoJSON Geometry Output / Export Available Available Available Available Available Available output GeoJSON string
ST_Azimuth Measurement Functions Available Available Available Available Available Available return azimuth in radians between two points
ST_Boundary Geometry Accessors Available Not available Available Available Available Available return combinatorial boundary
ST_ConvexHull Geometry Processing Available Not available Available Available Available Available compute convex hull
ST_DWithin Predicates / Topological Relationships Available Available Available Available Available Available test if within distance
ST_Envelope Geography Type Functions Available Available Available Not available Available Available bounding box for geography type
ST_Equals Predicates / Topological Relationships Available Not available Available Available Available Available test geometric equality
ST_ExteriorRing Geometry Accessors Available Not available Available Available Available Available return exterior ring of polygon
ST_GeometryType Geometry Accessors Available Not available Available Available Available Available return geometry type as string
ST_IsEmpty Geometry Accessors Available Not available Available Available Available Available test if geometry is empty
ST_MakeLine Geometry Editors Available Available Available Available Not available Available create linestring from points
ST_MakePolygon Geometry Editors Available Available Available Available Not available Available create polygon from shell + optional holes
ST_NumGeometries Geometry Accessors Available Not available Available Available Available Available return number of geometries in collection
ST_Point Geometry Constructors Available Available alias of ST_MAKEPOINT Available Not available Available Available create point from X,Y
ST_Simplify Geometry Processing Available Available Available Available Available Available use Douglas-Peucker simplification
ST_SRID Spatial Reference System Available Available Available Not available Available Available return SRID value
ST_Touches Predicates / Topological Relationships Available Not available Available Available Available Available test touch relationship
ST_Transform Spatial Reference System Available Available Available Not available Available Available reproject geometry; Wherobots supports source+target CRS
ST_AsEWKB Geometry Output / Export Available Available Available Not available Not available Available output EWKB (includes SRID)
ST_AsEWKT Geometry Output / Export Available Available Available Not available Not available Available output EWKT
ST_ClosestPoint Measurement Functions Available Not available Available Available Available Available return closest point on geom1 to geom2
ST_Collect Geometry Editors Available Available Available Not available Not available Available collects into multi-geometry
ST_Covers Predicates / Topological Relationships Available Available Available Available Not available Available test if A covers B
ST_GeoHash Geometry Output / Export Available Available Available Available Not available Available return geohash string
ST_GeometryN Geometry Accessors Available Not available Available Not available Available Available returns the Nth geometry in a collection
ST_HausdorffDistance Measurement Functions Available Available Not available Available Available Available Hausdorff distance with optional density
ST_InteriorRingN Geometry Accessors Available Not available Available Not available Available Available return Nth interior ring of polygon
ST_IsClosed Geometry Accessors Available Not available Not available Available Available Available checks if linestring is closed
ST_IsRing Geometry Accessors Available Not available Not available Available Available Available checks if closed and simple

Check marks link to each platform’s documentation for the function. Sources, checked October 2026: the Wherobots function reference, Snowflake geospatial functions, Databricks ST and H3 functions, BigQuery geography functions, ArcGIS GeoAnalytics Engine 2.1 SQL, raster and track functions, and the PostGIS 3.6 reference and raster reference (functions only; operators, version and management functions and the SFCGAL, Topology and Tiger extensions are left out).

Which platform fits your workload

Raster plus vector at scale

Wherobots fits teams whose work joins imagery, elevation or climate rasters with buildings, parcels, roads or assets, from one city to the whole planet. WherobotsDB runs zonal statistics and spatial joins in one engine, and RasterFlow turns imagery into features you can join.

Vector analysis inside your warehouse

Snowflake, Databricks and BigQuery fit teams adding point-in-polygon lookups, distance filters and H3 binning to data already in the warehouse, with no new platform to run.

Raster statistics on Google Cloud

BigQuery fits teams on Google Cloud that need statistics of Earth Engine rasters inside polygons, through ST_REGIONSTATS.

One PostgreSQL database

PostGIS fits applications and analysis that fit on one PostgreSQL server, such as a service that reads and writes features through the day.

Esri teams on their own Spark

ArcGIS GeoAnalytics Engine fits teams standardized on ArcGIS that already run Spark on Databricks, Amazon EMR, Azure Synapse or Google Cloud.

Cloud geospatial analytics platform FAQ

What is a cloud geospatial platform?

A cloud geospatial platform stores and analyzes location data on managed cloud compute. It has spatial types and functions for vector data, such as points, lines and polygons. Many also handle raster data, such as satellite imagery and elevation. See what geospatial data is and what a geospatial database is.

Which cloud geospatial database supports both vector and raster analysis?

WherobotsDB has native vector and raster types, so one spatial SQL query can compute raster statistics inside vector polygons. BigQuery does the same for Earth Engine rasters with ST_REGIONSTATS. See WherobotsDB and raster vs. vector data.

What are the top serverless options for spatial SQL analytics?

Wherobots Cloud runs WherobotsDB serverless, BigQuery is a serverless query service, and Databricks offers serverless SQL warehouses. Of these, Wherobots and BigQuery also query raster data.

Which cloud geospatial platforms support spatial SQL and Python?

All of the platforms on this page support spatial SQL. Wherobots runs the same spatial functions from SQL, Python and Scala, Databricks through PySpark, Snowflake through Snowpark Python, and BigQuery through BigQuery DataFrames.

Can RasterFlow results go into Snowflake, Databricks or BigQuery?

Yes. Wherobots writes RasterFlow results to Iceberg tables in Databricks Unity Catalog, to Apache Iceberg tables in your S3 bucket that Snowflake reads, and to GeoParquet that BigQuery loads. Google Earth Engine is the imagery platform RasterFlow compares with most often; see RasterFlow vs. Google Earth Engine.

Why do spatial joins get slow on general-purpose platforms?

A spatial join compares geometries by location, so an engine without spatial partitioning compares far more pairs than it needs to. See what a spatial join is and the partitioning tax.