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Wikigraph

an interactive visualization of all of English Wikipedia

Details

External ID
48370512
Source
HN
Company
—
Product
Wikigraph
Website domain
tobypenner.com
Launched
June 2, 2026
Cohort
—
Upvotes
12
Upvotes percentile
0.6509562841530054
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hi! This is a visualization I've always wanted but never quite found. It's a navigable map of the Wikipedia link graph structure, with search and shortest-path finding.Offline, I parsed the May 2026 English Wikipedia full-text dump into a directed graph, used cuGraph on a GPU to run PageRank, Leiden clustering, and ForceAtlas2 for the layout. I did some post processing to get rid of lingering overlapping nodes and rendered a tiled map of raster base images (using Skia) and JSON metadata. Tiles are bundled into PMTiles. The frontend is Deck.gl.Everything is hosted on Cloudflare. Search and shortest-path are served by a Rust backend in CF Containers which uses Tantivy and bidirectional BFS.Happy to answer any questions!

Enrichment

Theme
web development and browser utilities
Vertical
Media & entertainment
Function
Search & retrieval
Audience
B2C
AI stance
Not AI
Project type
Commercial product
Normalized one-liner
interactive visualization of wikipedia
Manually corrected
False

Could you build this?

Partial The web UI can be built easily, but processing English Wikipedia's dump into millions of graph nodes, running GPU Leiden clustering and PageRank, and creating a multi-scale spatial graph layout requires dedicated high-performance data pipelines.

What it would actually take: The backend data pipeline requires parsing massive Wikipedia XML/SQL dumps (tens of gigabytes), constructing a 6M+ node directed graph, and executing GPU-accelerated algorithms (via NVIDIA cuGraph or cuML) for PageRank, community detection (Leiden/Louvain), and force-directed or UMAP/t-SNE 2D spatial embedding. The frontend requires a high-performance WebGL graph renderer (such as Sigma.js or custom deck.gl/InstancedMesh) paired with spatial tiling (like vector tiles or quadtrees) to smoothly render millions of nodes. Specialized data engineering and GPU graph computation skills are necessary.

Discussion

2 comments analyzed.

Concerns raised: 2D visualization limits clustering fidelity compared to higher dimensions, Unclear whether 2D representation is necessary or just a choice

Feature requests: 3D or higher-dimensional visualization support

Competitors

Other products that read as similar to this one — 102 launches clear the similarity bar, closest 8 shown.

Attention rank: #42 of 103 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 213 days after the earliest competitor.

Other launches for this product