optimize-large-map-data

Marker clustering optimizes map performance by grouping dense markers into single visual clusters. It works alongside viewport-bounded RPC to reduce rendering load, ensuring smooth navigation with large datasets.

Viewport-bounded RPC improves map loading by efficiently querying only the data within the current visible map boundaries. This reduces network payload and rendering overhead when displaying large marker datasets.

Yes, you can use IndexedDB to persist large map datasets for quick access. Storing map data locally prevents redundant network requests and significantly speeds up map load times on subsequent visits.

The best way to handle map lag when zooming in on high density markers is using containment skip and adaptive tile sizing. These techniques dynamically adjust tile loads and skip unnecessary data processing during zoom.

Adaptive tile sizing helps with rendering large network maps by dynamically adjusting tile size based on the viewport span. This optimizes data fetching and ensures efficient rendering across varying zoom levels.