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🧮 Count-Min Sketch: Estimating Frequencies Without Storing Everything

Learn how the Count-Min Sketch estimates item frequencies in massive data streams using a fraction of the memory an exact hash-map counter would need.

Algorithms & AI3DModerate60 FPS

This simulator visualizes how items get hashed into a grid of counters across multiple rows, and how taking the minimum value across rows yields an accurate frequency estimate despite hash collisions.

🔬 What It Demonstrates

🎮 How to Use

Feed items into the stream, watch the counters increment across each row, and query an item to see how the minimum across rows produces its frequency estimate.

💡 Did You Know?

A Count-Min Sketch with just a handful of rows and a few thousand columns can accurately estimate frequencies across a stream containing hundreds of millions of distinct items.

⚙ Under the hood

Learn how the Count-Min Sketch estimates item frequencies in massive data streams using a fraction of the memory an exact hash-map counter would need.

count-min sketchprobabilistic data structuresstreaming algorithmshash functionsbig datafrequency estimationnetwork monitoringdatabase optimization

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