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QuickSight layer maps add Point and LineString support for location and route visualizations

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Amazon QuickSight layer maps now accept Point and LineString geometry types in GeoJSON files, extending the previous Polygon‑only capability. This change lets engineers embed individual sites and travel paths directly in dashboards, influencing data pipelines, dataset joins, and operational handling of geospatial assets.

QuickSight layer maps have been extended to recognize two additional GeoJSON geometry types—Point and LineString. Previously, only custom shape layers such as polygons could be rendered. The new support enables practitioners to plot discrete locations (stores, sensors, etc.) and trace routes (delivery paths, flight legs) without resorting to separate visualizations.

Supported Geometry Types and Data Model

The layer map still consumes a single GeoJSON file, now allowed to contain Point and LineString features alongside existing polygon definitions. Each feature follows the standard FeatureCollection envelope, with a geometry object that declares its type and coordinates. For a point, coordinates is a single [longitude, latitude] pair; for a line, it is an ordered array of such pairs.

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "geometry": { "type": "Point", "coordinates": [88.4, 22.6] },
      "properties": { "prop0": "value0" }
    },
    {
      "type": "Feature",
      "geometry": { "type": "LineString", "coordinates": [ [88.2,22.4], [88.9,23.1] ] },
      "properties": { "prop0": "value0" }
    }
  ]
}

Only the geometry type selected in the visual configuration is rendered, so a mixed file will display either points or lines, but not both simultaneously.

Dataset Integration and Join Keys

Layer maps still rely on a QuickSight dataset for metric values. The link between a GeoJSON feature and a dataset row is a shared key stored in the feature’s properties object and the dataset’s corresponding field. Field names may differ, but the values must match exactly. The dataset supplies the quantitative context (sales, latency, etc.) that is visualized on top of the geographic shape.

Prerequisites for a successful deployment include a valid .geojson file (max 100 MB), a QuickSight dataset with the required dimensions, and a consistent join key. The visual’s “Geometry type to visualize” setting determines which feature type is drawn, while the “Shape file key field” and “Dataset key field” settings establish the join.

Operational Considerations

Because the GeoJSON file is an external asset, teams must incorporate its lifecycle into CI/CD pipelines. Updating routes or adding new points requires regenerating the file and re‑uploading it to the QuickSight asset store, a step that can be automated via the QuickSight API. The 100 MB size limit may affect high‑resolution route data, prompting engineers to consider simplification or tiling strategies.

From a security perspective, the GeoJSON file inherits the same access controls as any other QuickSight resource. Practitioners should ensure that only authorized roles can modify or replace the file, as changes directly affect the visual output and could expose sensitive location data.

Related CloudNinjas coverage: AWS.

What This Means For Practitioners

  • Update data pipelines to generate Point or LineString features alongside any existing polygons, ensuring the join key is present in each feature.
  • Review QuickSight dataset schemas to include the matching key field and any metrics you wish to overlay on the map.
  • Incorporate GeoJSON regeneration into automated deployment workflows to keep route visualizations current without manual steps.
  • Validate that IAM policies governing QuickSight assets restrict write access to the GeoJSON file to trusted service accounts.
  • Monitor file size and coordinate simplification techniques if route detail approaches the 100 MB limit.
Originally published atAWS Machine Learning Blog