/mapbox-google-maps-migration

Data Updates, Performance, and Common Migration Patterns

Data Updates

Google Maps

// Update marker position
marker.setPosition({ lat: 37.7849, lng: -122.4094 });

// Update polygon path
polygon.setPath(newCoordinates);

Mapbox GL JS

// Update source data
map.getSource('points').setData(newGeojsonData);

// Or update specific features
const source = map.getSource('points');
const data = source._data;
data.features[0].geometry.coordinates = [-122.4094, 37.7849];
source.setData(data);

Performance Considerations

Google Maps

• Individual objects for each feature
• Can be slow with 1000+ markers
• Requires MarkerClusterer for performance

Mapbox GL JS

• Data-driven rendering
• WebGL-based (hardware accelerated)
• Handles 10,000+ points smoothly
• Built-in clustering

Migration Tip: If you have performance issues with Google Maps (many markers), Mapbox will likely perform significantly better.

Common Migration Patterns

Pattern 1: Store Locator

Google Maps approach:

1. Create marker for each store
2. Add click listeners to each marker
3. Show info window on click

Mapbox approach:

1. Add all stores as GeoJSON source
2. Add symbol layer for markers
3. Use layer click event for all markers
4. More performant, cleaner code

Pattern 2: Drawing Tools

Google Maps:

• Use Drawing Manager library
• Creates overlay objects

Mapbox:

• Use Mapbox Draw plugin
• More powerful, customizable
• Better for complex editing

Pattern 3: Heatmaps

Google Maps:

const heatmap = new google.maps.visualization.HeatmapLayer({
  data: points,
  map: map
});

Mapbox:

map.addLayer({
  id: 'heatmap',
  type: 'heatmap',
  source: 'points',
  paint: {
    'heatmap-intensity': 1,
    'heatmap-radius': 50,
    'heatmap-color': ['interpolate', ['linear'], ['heatmap-density'], 0, 'rgba(0,0,255,0)', 0.5, 'lime', 1, 'red']
  }
});