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---
title: Prolly Tree Visualizer | daily.dev
description: An interactive Prolly Tree visualizer has been built at prollytree.com, powered by DoltLite running entirely in the browser via WebAssembly. Unlike simulated...
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og:title: Prolly Tree Visualizer | daily.dev
og:description: An interactive Prolly Tree visualizer has been built at prollytree.com, powered by DoltLite running entirely in the browser via WebAssembly. Unlike simulated...
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# Prolly Tree Visualizer

**[DoltHub Blog](https://daily.dev/sources/dolthub-blog)** · 10 min read · 3 upvotes · 0 comments

## Summary

An interactive Prolly Tree visualizer has been built at prollytree.com, powered by DoltLite running entirely in the browser via WebAssembly. Unlike simulated demos, every insert, update, and delete is real SQL executed against DoltLite WASM, with the visualizer decoding actual on-disk chunk formats to render SVG trees. The tool demonstrates four core Prolly Tree properties: B-tree-like read/write performance, fast diff (work proportional to change size, not table size), structural sharing (unchanged chunks reused across versions), and history independence (same key-value pairs always produce identical chunk boundaries regardless of insertion order). Built with help from Codex in about eight hours, the visualizer includes tabs for modification, lookup animation, fast diff comparison, storage accounting, history independence verification, and chunk boundary inspection. The source is open on GitHub.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://dolthub.com/blog/2026-08-10-prolly-tree-visualizer>

## Questions this post answers

### What is a Prolly Tree and why is it useful for version-controlled databases?

A Prolly Tree is an immutable, content-addressed tree structure that gives B-tree-like read/write performance while adding fast diff, structural sharing, and history independence. Content-defined chunking derived from key hashes means chunk boundaries depend only on the data, not insertion order, so unchanged chunks are shared across versions and identical row sets always produce the same chunk boundaries and root address.

_daily.dev surfaces deep dives like this for engineers evaluating version-controlled database internals._

### How does fast diff work in a Prolly Tree compared to scanning the whole table?

Fast diff compares root addresses first; if they match the trees are identical and the diff stops immediately. If they differ, it opens the roots and compares child addresses, skipping any subtree whose address matches and descending only into changed ones until it reaches the modified leaves. Work scales with the size of the change rather than the size of the table, which is what makes diffing large version-controlled databases practical.

_track how database diffing techniques evolve by following storage-engine deep dives on daily.dev._

### How much of a Prolly Tree visualizer's code was written by an AI coding agent like Codex versus a human?

Codex wrote the TypeScript, SVG layout, animation, tooltips, tests, and CSS for the visualizer, while the human supplied only the product direction: make the existing Prolly Tree explanation interactive, use the real DoltLite engine, and expose every important tree property. The whole build took about eight hours of back-and-forth, with the storage format and DoltLite's existing tests acting as a hard specification for the agent.

_daily.dev helps developers gauge what agentic coding tools like Codex can realistically ship._

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---

Tags: [#backend](https://daily.dev/tags/backend), [#webassembly](https://daily.dev/tags/webassembly), [#data-structures](https://daily.dev/tags/data-structures)

[View this post on daily.dev](https://daily.dev/posts/prolly-tree-visualizer-ncidopbgv)

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