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🗄️ Database Design Lab: Normalization, Indexing & Joins

A 3D relational database you can restructure live: split or merge tables to see normalization trade-offs, toggle a B-tree index, switch between SQL and NoSQL document models, and run a query to watch it traverse rows and joins.

AI & Machine Learning3DAdvanced60 FPS

A live, editable 3D database: reshape a small orders schema between normalized and denormalized form, switch between relational and NoSQL document models, toggle a B-tree index, and run a query to watch it physically travel through rows, index nodes and foreign-key joins.

🔬 What It Demonstrates

Normalization removes duplicate data by splitting it across linked tables; denormalizing trades that redundancy for simpler reads. Indexing turns a linear scan into a logarithmic lookup, and NoSQL documents avoid joins by embedding related data directly.

🎮 How to Use

Pick a table structure and data model, set how much data each table holds, toggle the index on or off, then press Run query and watch the glowing pulse trace its path — and read off how many rows it had to examine.

💡 Did You Know?

A composite B-tree index can turn a query that reads millions of rows into one that reads a few dozen — but every index also has to be updated on every write, which is the classic read/write trade-off in database design.

⚙ Under the hood

machine learningdata modelingdatabasenormalizationindexingjoinsThree.js

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