Visualize points and routes with GeoJSON in Amazon Quick Sight layer maps

Amazon Quick Sight layer maps can display both fixed locations and routes from GeoJSON: Point features mark places, while LineString features draw ordered paths. Each feature needs a key that matches a row in a Quick Sight dataset, which supplies metrics and tooltip details. This is a map visualization capability; the AWS article does not say the map itself optimizes routes or dispatches vehicles.

What data does the map need?

AWS specifies a GeoJSON file for the geometry, a Quick Sight dataset for the business data, and a shared join key. A store Point can carry a store ID in its properties; a route LineString can carry a route ID. The matching dataset row provides values such as store performance or route details. Coordinates for a Point are given as longitude and latitude, while a LineString contains an ordered list of coordinate pairs.

A layer renders one geometry type at a time. If the same file contains points, lines and polygons, select the type for each layer. AWS documents a 100 MB maximum for the GeoJSON file in this workflow. Check the source article and current product documentation when planning a large map.

When should you use a Point layer?

A Point layer is useful for curated, relatively fixed locations such as stores or depots, especially when the viewport must stay locked or points need to sit alongside other geometry. It uses explicit coordinates and a uniform marker size. The joined dataset can still drive color and tooltip content.

Quick Sight's native point map is different: it can geocode location names, refresh locations from SPICE or Direct Query, and support clusters or heatmaps. If locations move often, that native visual may fit better. AWS makes this distinction in its Quick Sight walkthrough.

What changes when routes or locations change?

Refreshing the dataset updates metrics, not the coordinates stored in GeoJSON. To change a route or place, replace the GeoJSON and republish the dashboard. AWS describes a manual upload for infrequent changes and an API route for dynamic updates: put the new file in S3, update the dashboard definition's spatial file reference, call UpdateDashboard, then publish with UpdateDashboardPublishedVersion.

That distinction matters for a logistics dashboard or business intelligence system. A map showing yesterday's route geometry alongside today's metrics can mislead. Define who owns geometry updates, how join keys are validated and when a new dashboard version becomes visible before treating the map as an operational view. These are implementation checks, not reported MTREXA client results.

Source and attribution

This MTREXA editorial explanation is based on AWS's “Visualize points and routes with GeoJSON in Amazon Quick Sight layer maps”, by Amit Makashir, Koushik Muthanna Koravanda Ganapathy, Jackson Dowden and Salim Khan, published October 23, 2026. Product behavior and examples are attributed to AWS; the operational checks above are MTREXA's interpretation.