Products

Datafold

AI-nativeMCP

Automate Data Engineering

datafold.com Source★ 58MITSoftware Development / Testing & Code Quality

AI Benchmark
Desktop
Mobile
Monthly visits
19.5K
Down13.2%MoMSep 2026
Public revenue
Undisclosed
No public revenue evidence yet
Entry price
Free
No monthly subscription pricing
Creators
hichkaker
@datafoldcom· 1,092 followers
Launched
6y ago
2020-08-07 · Est.

Traffic

Monthly visitsData through Sep 2026 · Oct 2026 pending
Events12 changes

Marketing moves

Launches, search & content, referrals, promotions
X accounts@datafoldcom
  • Launched on Show HN (3 pts · 1 comments)Launch

    Audit dbt models as you code

    Apr 24, 2023 · 3y agoLaunch page

  • Launched on Show HN (127 pts · 21 comments)Launch

    Data Diff – compare tables of any size across databases — Gleb, Alex, Erez and Simon here – we are building an open-source tool for comparing data within and across databases at any scale. The rep…

    Jun 22, 2022 · 4y agoLaunch page

  • Launched on Product HuntLaunch

    Quality assurance & monitoring for analytical data

    Aug 7, 2020 · 6y agoLaunch page

Third-party reviews & case dossiers

Acquisition breakdowns, engineer reviews & open-source metrics
Show HN
2022-06-22Source
Post excerpt:
Gleb, Alex, Erez and Simon here – we are building an open-source tool for comparing data within and across databases at any scale. The repo is at https://github.com/datafold/data-diff , and our home page is https://datafold.com/ . As a company, Datafold builds tools for data engineers to automate the most tedious and error-prone tasks falling through the cra

Open Source & Agent Ecosystem

GitHub · MCP / Skill
Last commit 2026-05-25
GitHub Stars
★ 58
Forks
28
License
MIT
Primary language
Python

Agent, MCP & Developer Integration

MCP Server
Integration docs
Browse all MCP Server products →

Traffic sources

Sep 2026

Traffic breakdown

Channels

  • Direct41%
  • Organic Search32%
  • Referrals10%
  • Social6%
  • Other10%

Countries

  • United States46%
  • United Kingdom9%
  • India8%
  • Vietnam5%
  • France5%

Search

Domain authority —Domain registered 2017-08-10

KeywordMonthly volume
ci131.7K
datafold1,260
data reconciliation830
database diff510
datafold data-diff—

Traffic data: Vaneform

Pricing

Pricing page does not list plan prices.

Trial: None · Observed 2026-11-04 · Pricing page

Pages & changes

Tracked since 2020-08-07

Key pages

Weekly snapshots

Changes

  1. Nov 1 · 13d ago

    Homepage headline (H1) changed to “Automate Data Engineering”Positioning

    The migration | platform for data engineering teams→Automate Data Engineering

  2. Nov 1 · 13d ago

    Adopted technology: Amazon CloudFrontFeatures

    —→Amazon CloudFront

  3. Nov 1 · 13d ago

    Adopted technology: AstroFeatures

    —→Astro

  4. Nov 1 · 13d ago

    Removed technology: Highlight.jsFeatures

    Highlight.js→—

  5. Nov 1 · 13d ago

    Removed technology: LeadfeederFeatures

    Leadfeeder→—

  6. Nov 1 · 13d ago

    Removed technology: LiveIntentFeatures

    LiveIntent→—

Design

First-screen visual analysis & :root CSS

Minimal Monochrome (Light canvas, airy density) featuring centered headline + cta layout and pure typography & geometry visuals.

First-screen preview · click to zoom

First-screen pitch & conversion flow

“Automate Data Engineering”

Centered Headline + CTA hero structure paired with email capture / waitlist CTA and customer / press logo strip.

Conversion path: Centered Headline + CTA + Pure Typography & Geometry → Email Capture / Waitlist · Trust bar: Customer / Press Logo Strip

Palette · click to copy

5-D design score7.5 / 10
Typography
8.0
Color & Contrast
8.0
Layout & Spacing
8.0
Craft & Polish
7.0
Distinctiveness
6.0

Structure

Fonts
Arial / Courier New
Primary visual
Pure Typography & Geometry
Social proof
Customer / Press Logo Strip
Navigation
Full-Width Top Bar
Theme & density
Light · Airy
Corners & depth
Small Radius · Hairline borders
Preview full AI design brief (includes :root CSS variables & layout rules)Style tokens only; never copy brand names, logos, copy, or images
# Design Brief: Minimal Monochrome (with Enterprise Clean)

Monochrome palette with a single accent color, hairline dividers, and generous whitespace.

## Design Tokens

```css
:root {
  --background: #ffffff;
  --surface: #ffffff;
  --foreground: #181818;
  --muted-foreground: #777777;
  --accent: #376bf5;
  --radius: 4px;
  --font-heading: "Arial", ui-sans-serif, system-ui, sans-serif;
  --font-body: "Arial", ui-sans-serif, system-ui, sans-serif;
  --font-mono: "Courier New", ui-sans-serif, system-ui, sans-serif;
}
```

Color area ratio: Background #FFFFFF (~79%) · Surface #FFFFFF (~6%) · Text #181818 (~7%) · Muted Text #777777 (~4%) · Accent #376BF5 (~4%). Background and surface dominate the canvas; reserve the accent color for primary buttons and active states.

## Layout & Conversion Structure

- Hero layout: Centered Headline + CTA
- Navigation: Full-Width Top Bar
- Theme & density: Light · Airy
- Border radius & elevation: Small Radius; no drop shadows—separate layers with hairline borders and whitespace
- Primary visual medium: Pure Typography & Geometry
- Conversion CTA: Email Capture / Waitlist · Trust bar uses Customer / Press Logo Strip
- Headline hook: Category Positioning Anchor
- Hero components: Customer Logo Wall
- Spatial layout notes: Centered Headline + CTA hero structure paired with email capture / waitlist CTA and customer / press logo strip.
- Visual summary: Minimal Monochrome (Light canvas, airy density) featuring centered headline + cta layout and pure typography & geometry visuals.

## Avoid

- Multi-stop neon gradients
- Heavy drop shadows
- More than one competing accent color

Implement the UI following the design tokens and layout specifications above: use only these color variables, and reserve the accent color strictly for primary actions and active states. Adopt only this visual style—never copy any reference product’s brand name, logo, copy, or imagery.

Questions & evidence

How much website traffic does Datafold get?
Vaneform estimates 19.5K website visits in 2026-09. Visits can include repeat visits; this estimate measures web traffic separately from paying customers or revenue.Source
What is Datafold and what platforms does it support?
Datafold is catalogued under Testing & Code Quality: Automate Data Engineering. Supported platforms: MCP Server.
Is Datafold open source?
Datafold has a public repository (https://github.com/datafold/data-diff) under the MIT license, recording 58 GitHub stars.Source

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