> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wherobots.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Wherobots Platform Overview

> Understand how WherobotsDB, GeoStats, Map Matching, RasterFlow, and Havasu work together to power spatial analytics at planetary scale

Wherobots is a cloud-native platform purpose-built for creating data products from spatial data.

Built by the creators of [Apache Sedona](https://sedona.apache.org), Wherobots brings together spatial analytics, AI, and data management into a single, serverless platform.

<Tip>
  **Ready to get started?** [Create a free Community Edition account](/get-started/wherobots-cloud/create-account) and [run your first notebook](/get-started/wherobots-cloud/start-notebook) in minutes.
</Tip>

## Core products

Wherobots has the following core products, which when used together provide a comprehensive platform for spatial data processing, analytics, and AI:

<CardGroup cols={2}>
  <Card title="WherobotsDB" icon="database" href="/get-started/wherobots-fundamentals/platform-overview#wherobotsdb-in-depth">
    **Spatial analytics engine**

    Cloud-native, serverless engine for querying and processing geospatial data. Supports Spatial SQL, Python, and Scala with 300+ vector and raster functions. Apache Sedona-compatible.

    * Process vector and raster data at planetary scale
    * Up to 20x faster than alternatives
    * Open formats: Parquet, GeoParquet, GeoTIFF
  </Card>

  <Card title="GeoStats & Map Matching" icon="brain" href="/get-started/wherobots-fundamentals/platform-overview#geostats-and-map-matching-in-depth">
    **Spatial algorithms**

    Detect spatial patterns with statistical algorithms and match GPS traces to road networks.

    <br />

    <br />

    * GeoStats: DBSCAN, Getis-Ord Gi\*, Local Outlier Factor
    * Map Matching: GPS-to-road-network alignment
  </Card>

  <Card title="RasterFlow" icon="layer-group" href="/develop/rasterflow/index">
    **Raster processing & inference engine** <Badge color="purple" size="sm">Private Preview</Badge>

    End-to-end pipeline for large-scale raster workflows. Build mosaics from satellite imagery, run ML model inference, and vectorize results.

    <br />

    <br />

    * Pre-configured models for land cover, roads, canopy height
    * Bring your own data and models
    * Simple, high-level API
  </Card>

  <Card title="Havasu" icon="table" href="/reference/havasu-table/introduction">
    **Spatial table format**

    Built on Apache Iceberg, Havasu adds native support for geometry and raster data types. ACID transactions, schema evolution, time travel, and partition pruning for spatial workloads.

    <br />

    * Geometry and raster column types
    * Spatial filter push-down
    * Iceberg-compatible tooling
  </Card>
</CardGroup>

## WherobotsDB in depth

WherobotsDB is a cloud-native, serverless analytics engine optimized for geospatial workloads.

<AccordionGroup>
  <Accordion title="Key capabilities" icon="list-check">
    * **Modern, performant, and affordable**: Run small to planetary-scale geospatial queries up to 20x faster, at a fraction of the cost. Only pay for what you use.
    * **Unified vector and raster**: Derive insights through spatial relationships between vector and raster data types in a single engine.
    * **Apache Sedona compatible**: Lift-and-shift Sedona workloads with confidence.
    * **Popular languages**: Spatial SQL, Python, and Scala. No esoteric tools required.
    * **No vendor lock-in**: Open formats (Parquet, GeoParquet), Apache Iceberg, and your own cloud storage.
    * **Feature complete**: 300+ vector and raster functions, notebooks for Exploratory Data Analysis (EDA), production-ready job runs, and a geospatial dataset catalog.
    * **Serverless and secure**: No infrastructure management. 99.5% runtime SLA with isolation by default [for Enterprise Edition Organizations](/get-started/organization-management/organization-editions#enterprise-edition-organization).
  </Accordion>

  <Accordion title="Common use cases" icon="bullseye">
    * **Automating spatial data processing**: Schedule and automate ETL with Job Runs. Orchestrate pipelines with the [Wherobots Airflow Provider](/develop/airflow-provider).
    * **Modernizing Spark + Sedona workloads**: Eliminate cluster management, performance tuning, and indexing overhead. Lift-and-shift existing Sedona-on-Spark workloads.
    * **Extracting insights from aerial imagery**: [RasterFlow](/develop/rasterflow/index) integrates with WherobotsDB for end-to-end raster processing, ML inference, and analysis workflows.
  </Accordion>

  <Accordion title="Getting started" icon="rocket">
    The fastest way to start is to run an example notebook:

    1. [Create a free Community Edition account](/get-started/wherobots-cloud/create-account).
    2. [Start a runtime](/get-started/wherobots-cloud/start-notebook) and open `examples/Getting_Started/Part_1_Loading_Data.ipynb`.

    This notebook introduces the Wherobots Data Catalogs, Spatial SQL, and geospatial visualization.

    Already have existing workloads? Use `WherobotsRunOperator` to [run them as Job Runs from Airflow](/develop/run-operator).
  </Accordion>
</AccordionGroup>

## GeoStats and Map Matching in depth

GeoStats and Map Matching make it easy to extract insights from geospatial data without needing to be a geospatial or infrastructure expert.

<AccordionGroup>
  <Accordion title="GeoStats" icon="chart-scatter">
    Distributed ML clustering algorithms for detecting hotspots, density patterns, and local outliers in vector data.

    **Use cases:** pedestrian activity hotspots, public health outbreak detection, strategic retail placement.

    **Algorithms:** DBSCAN, Getis-Ord Gi\*, Local Outlier Factor.

    ```py theme={"system"}
    sedona = SedonaContext.create(config)
    clusters_df = dbscan(df, 0.3, 10, include_outliers=True)
    ```

    GeoStats is available in all Organization Editions, including Community (free).
  </Accordion>

  <Accordion title="Map Matching" icon="route">
    Offline distributed map matching — precisely align GPS or location-tracking coordinates to digital road networks.

    **Use cases:** traffic pattern analysis, optimized routing.

    ```py theme={"system"}
    sedona = SedonaContext.create(config)
    df_edge = matcher.load_osm("data/osm.xml", "[car]")
    result_df = matcher.match(df_edge, df_paths, "geometry", "geometry")
    ```

    Map Matching is available in all Organization Editions. Community Edition may experience latency with large datasets.
  </Accordion>

  <Accordion title="Edition availability" icon="table">
    |          Capability          | Community |                            Professional                           |                             Enterprise                            |
    | :--------------------------: | :-------: | :---------------------------------------------------------------: | :---------------------------------------------------------------: |
    | GeoStats (DBSCAN, LOF, Gi\*) |    Yes    |                                Yes                                |                                Yes                                |
    |         Map Matching         |    Yes    |                                Yes                                |                                Yes                                |
    |          RasterFlow          |     No    | Yes<br /> <Badge color="purple" size="sm">Private Preview</Badge> | Yes<br /> <Badge color="purple" size="sm">Private Preview</Badge> |

    **Example notebooks:**

    | Capability           | Notebook Path                                        |
    | :------------------- | :--------------------------------------------------- |
    | DBSCAN               | `examples/Analyzing_Data/Clustering_DBSCAN.ipynb`    |
    | Local Outlier Factor | `examples/Analyzing_Data/Local_Outlier_Factor.ipynb` |
    | Getis-Ord Gi\*       | `examples/Analyzing_Data/Getis_Ord_Gi*.ipynb`        |
    | Map Matching         | `examples/Analyzing_Data/GPS_Map_Matching.ipynb`     |
  </Accordion>
</AccordionGroup>

## How the products work together

Wherobots products can be used independently but are most effective when combined. Here are some common patterns for how customers use them together to build spatial data products:

<AccordionGroup>
  <Accordion title="Spatial ETL Pipeline" icon="arrows-rotate">
    **WherobotsDB + Havasu + Airflow**

    Ingest raw spatial data from S3 or public sources, transform with Spatial SQL, and store in Havasu tables for efficient querying. Automate your ETL with the [Wherobots Airflow Provider](/develop/airflow-provider).

    Typical flow: **Data Source** → **WherobotsDB** (transform) → **Havasu** (store) → **Downstream consumers**
  </Accordion>

  <Accordion title="Satellite Imagery Analysis" icon="satellite">
    **RasterFlow + WherobotsDB**

    Use RasterFlow to build mosaics from satellite imagery, run ML inference (classification, segmentation, object detection) with pre-configured or custom models, and vectorize the results. Then analyze and enrich the output with WherobotsDB.

    Typical flow: **Satellite imagery** → **RasterFlow** (mosaic + infer + vectorize) → **WherobotsDB** (analyze vectors) → **Visualization**
  </Accordion>

  <Accordion title="Location Intelligence" icon="location-dot">
    **WherobotsDB + GeoStats**

    Load point-of-interest or movement data, enrich with spatial joins, and detect clusters, hotspots, or anomalies using GeoStats algorithms.

    Typical flow: **Vector data** → **WherobotsDB** (join + enrich) → **GeoStats** (cluster) → **Insights**
  </Accordion>

  <Accordion title="Traffic & Routing Analysis" icon="route">
    **WherobotsDB + Map Matching**

    Load GPS traces, match them to road network geometries, and analyze traffic patterns, congestion, or optimal routes.

    Typical flow: **GPS data + road network** → **Map Matching** → **WherobotsDB** (analyze) → **Routing decisions**
  </Accordion>
</AccordionGroup>

### Key security properties

Wherobots is designed with security as a top priority. Wherobots has the SOC 2 Type 2 attestation.

For the full details, see the [Security Guide](/security-guide) and [Wherobots Trust Center](https://trust.wherobots.com).

## Workload types

Wherobots has the following workload types, each optimized for different use cases:

<Columns cols={2}>
  <Card title="Notebooks" icon="book-open" href="/develop/notebook-management/notebook-instance-management" horizontal>
    Interactive Jupyter notebooks for exploratory data analysis, prototyping, and visualization
  </Card>

  <Card title="Job Runs" icon="gears" href="/reference/runs" horizontal>
    Scheduled or ad-hoc batch jobs for production ETL, analytics, and Machine Learning workloads
  </Card>
</Columns>

<Columns cols={2}>
  <Card title="SQL Sessions" icon="code" href="/develop/spatial-sql-api" horizontal>
    Submit Spatial SQL queries programmatically to run ad-hoc analyses or power applications with a spatial SQL backend
  </Card>

  <Card title="MCP Server" icon="message-bot" href="/develop/mcp/mcp-server-usage" horizontal>
    Natural language interface for exploring spatial data in VS Code Copilot. MCP Server query executions are logged as SQL Sessions.
  </Card>
</Columns>

## Data connectivity

Wherobots connects to your data wherever it lives.

<Columns cols={3}>
  <Card title="Managed Storage" icon="database" href="/develop/storage-management/managed-storage" horizontal>
    Built-in storage included with every organization
  </Card>

  <Card title="Amazon S3" icon="hard-drive" href="/develop/storage-management/s3-storage-integration" horizontal>
    Bring your own S3 buckets with cross-account IAM roles
  </Card>

  <Card title="Unity Catalog" icon="link" href="/get-started/initial-storage/connect-to-unity-catalog" horizontal>
    Access Databricks Unity Catalog Delta tables directly
  </Card>
</Columns>

## Supported languages & formats

| Category           | Supported                                                |
| :----------------- | :------------------------------------------------------- |
| **Languages**      | Spatial SQL, Python, Scala                               |
| **Vector formats** | Parquet, GeoParquet, GeoJSON, Shapefile, GeoPackage, CSV |
| **Raster formats** | GeoTIFF, COG, NetCDF, Zarr                               |
| **Table formats**  | Apache Iceberg (Havasu), Delta Lake (via Unity Catalog)  |
| **Tile formats**   | PMTiles (vector tiles)                                   |
| **APIs**           | STAC, REST                                               |

## Organization editions

Wherobots offers three tiers to match your needs:

| Feature           | Community (Free) |                            Professional                           |                             Enterprise                            |
| :---------------- | :--------------: | :---------------------------------------------------------------: | :---------------------------------------------------------------: |
| WherobotsDB       |        Yes       |                                Yes                                |                                Yes                                |
| GeoStats          |        Yes       |                                Yes                                |                                Yes                                |
| RasterFlow        |         -        | Yes<br /> <Badge color="purple" size="sm">Private Preview</Badge> | Yes<br /> <Badge color="purple" size="sm">Private Preview</Badge> |
| SSO / SAML        |         -        |                                 -                                 |                                Yes                                |
| Dedicated support |         -        |                                 -                                 |                                Yes                                |

For full details, see [Organization Editions](/get-started/organization-management/organization-editions) and [Wherobots Pricing](https://wherobots.com/pricing/).

## Next steps

<Columns cols={3}>
  <Card title="Create an Account" icon="user-plus" href="/get-started/wherobots-cloud/create-account">
    Get started with a free Community Edition organization
  </Card>

  <Card title="Run a Notebook" icon="rocket" href="/get-started/wherobots-cloud/start-notebook">
    Launch your first spatial analytics notebook
  </Card>

  <Card title="Explore Tutorials" icon="graduation-cap" href="/tutorials/index">
    Hands-on guides for every Wherobots capability
  </Card>
</Columns>