Home▸Algorithms & AI▸T-Digest: Streaming Quantile Estimation

📊 T-Digest: Streaming Quantile Estimation

Stream a large data distribution through the t-digest algorithm's adaptive centroid merging and compare its estimated percentiles against exact values as the centroid budget changes.

Algorithms & AI3DModerate60 FPS

The simulation streams synthetic data points through a live t-digest, visualizing centroids forming and merging with denser clustering near the tails, then plots estimated percentiles against the true exact percentiles computed from the full dataset.

🔬 What It Demonstrates

🎮 How to Use

Choose a distribution shape and stream size, adjust the compression slider to change the centroid budget, and watch the error between estimated and exact percentiles shrink or grow as centroids are added or removed.

💡 Did You Know?

A t-digest with only a couple hundred centroids can estimate the 99.9th percentile of a stream of a billion values with error small enough for production monitoring, using a memory footprint thousands of times smaller than storing the raw data.

⚙ Under the hood

Stream a large data distribution through the t-digest algorithm's adaptive centroid merging and compare its estimated percentiles against exact values as the centroid budget changes.

t-digestquantilesstreaming algorithmspercentilesdata sketchesapproximation algorithmsmonitoringstatistics

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install