Apache Superset Geospatial Visualizations 2026

Apache Superset offers very powerful geospatial visualizations via Mapbox and Deck.gl: choropleth, scatter, heatmap, 3D hexagons. For data with coordinates or administrative zones, it's the tool of choice. This guide details the options in 2026.

1. Geo visualization types

Type	Use case
Country Map	Data per country
Choropleth Map	Density per administrative zone (departments, states)
MapBox	Custom map with geolocated points
Deck.gl Scatter	Millions of points (sensors, deliveries)
Deck.gl 3D Hexagon	3D density, spatial exploration
Deck.gl Arc	Oriented links (origin/destination)
Deck.gl Geojson	Custom polygons (catchment areas)

If you want geospatial templates, TVL Managed Superset offers preconfigured geo dashboards.

2. Mapbox prerequisites

Mapbox/Deck.gl visualizations require an access token:

1. Create an account on mapbox.com;
2. Retrieve the default public token;
3. Add it in superset_config.py:

MAPBOX_API_KEY = os.environ["MAPBOX_API_KEY"]

3. Geo data model

CREATE TABLE fct_orders_geo (
  order_id UUID PRIMARY KEY,
  customer_id INT,
  amount DECIMAL,
  latitude DOUBLE PRECISION,
  longitude DOUBLE PRECISION,
  country_code VARCHAR(2),
  region VARCHAR,
  postal_code VARCHAR,
  created_at TIMESTAMP
);

CREATE INDEX idx_orders_country ON fct_orders_geo(country_code);

4. Country Map

To visualize data per country:

1. Chart type: Country Map;
2. Select country: France, Germany, USA...;
3. ISO 3166-1 alpha-2 or alpha-3 in the data;
4. Metric: SUM(amount), COUNT(*).

5. Choropleth Map (departments/states)

For France:

1. Chart type: Choropleth Map;
2. Region type: France Départements;
3. Region column: department code (01, 02, ..., 95);
4. Metric: SUM(amount).

This configuration is applied by default on TVL Managed Superset, which follows community best practices.

6. Deck.gl Scatter for millions of points

When you have many points (deliveries, IoT sensors):

1. Chart type: deck.gl Scatter;
2. Latitude / Longitude columns;
3. Point size, color (per segment);
4. Filter by time range to display progressively.

Deck.gl uses WebGL and handles 10-100 million points in browser.

7. Deck.gl 3D Hexagon

To visualize point density (deliveries per zone):

• Hexagons of N meters radius;
• 3D height = number of points in the hexagon;
• Color = other metric (average basket, for example);
• Drill-down possible.

8. Iconic use cases

• E-commerce: delivery map, warehouse optimization;
• Mobility: trips, friction points;
• Public: territorial open data;
• Marketing: catchment areas, performance per region;
• IoT: real-time geolocated sensors.

9. Performance

• Pre-aggregation per H3 hexagon or geohash in dbt;
• Aggressive Redis cache on stable dashboards;
• Mapbox tile caching via paid subscription if high traffic;
• Filter time range mandatory on large tables.

10. Common pitfalls

• Missing Mapbox token: blank map;
• Mapbox quota exceeded (50k loads/month free tier);
• Inverted lat/lng data: 30% of datasets have the error;
• Department codes with/without leading 0 → mismatch;
• Non-WGS84 SRS: Superset expects lat/lng in degrees, not Lambert meters.

11. Conclusion

Apache Superset offers impressive geospatial coverage for a free BI tool. For most needs (maps per country, departments, geolocated points), it's an excellent choice over Tableau or Power BI. For very advanced analyses (routing, isochrones), dedicated tools (Carto, Kepler.gl) remain more powerful.

Want the benefits of Apache Superset without the friction of installation and maintenance? Deploy your instance in 3 clicks with TVL Managed Superset, hosted in Europe (OVHcloud, Roubaix, France).

For more: Deck.gl, chart types, real-time IoT.