H3

Health v2 · maintenance only

Adoption not part of the score

6495 stars · 613 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

H3 is a hexagonal hierarchical geospatial indexing system developed at Uber, implemented as a C core library with bindings for many languages including JavaScript, Python, Java, and Go. It partitions the globe into hexagonal cells across 16 resolutions, enabling spatial joins, aggregation, nearest-neighbor, and flow modeling on geographic data.

Use cases

• index latitude/longitude points into hexagonal grid cells
• aggregate and join disparate geospatial datasets at different resolutions
• find neighbors and grid distance between hex cells
• bin coordinates into hexagons for map visualizations
• prepare geospatial features for machine learning
• model flows and shortest paths on a hex grid
• convert between coordinates and cell boundaries/polygons

When to choose

• you need a hierarchical discrete global grid with hexagonal cells
• you want fast spatial joins or aggregation across datasets
• you need multi-resolution indexing from city-scale to meter-scale
• you want bindings across many languages backed by a fast C core

When to avoid

• you need exact geometric containment between parent and child cells (H3 only guarantees approximate containment)
• you need precise polygon coverage or raster reprojection rather than point/cell indexing
• you need a full GIS toolkit rather than a grid indexing library

Facets

library · maturity stable

geospatial sdk cli developer-tools data-science analytics cross-platform c python go jvm rust cli hexagonal-grid spatial-indexing discrete-global-grid-system hierarchical-indexing geohashing spatial-join uber geospatial maps algorithms javascript

Member repositories

For agents

markdown · JSON · MCP: product_card(name="uber/h3")