WikiKeebs

Worlds Largest Keyboard Database

ReactMongoDBExpressNode.jsTailwindCSSDatabase Design
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WikiKeebs

Project Overview

WikiKeebs is a comprehensive mechanical keyboard database built as a resource for keyboard enthusiasts, collectors, and professionals — detailed specifications, user reviews, price comparisons, and interactive 3D previews.

Built as a community-driven platform, WikiKeebs combines data aggregation from multiple sources with a modern web frontend to make browsing thousands of keyboard listings fast and easy.

Our Role

Hexed led the complete development and design of WikiKeebs, building the full-stack application and backend infrastructure from scratch.

  • Full-stack MERN development (MongoDB, Express, React, Node.js)
  • Database architecture and schema design for a large, growing keyboard catalog
  • Three.js integration for interactive 3D keyboard previews
  • Python microservices for automated data fetching and processing

Platform Experience

WikiKeebs HomepageWikiKeebs Keyboard DetailsWikiKeebs GuideWikiKeebs 3D Preview

Services Provided

Full-Stack Development

Built a MERN stack application — React frontend, Node.js/Express backend, MongoDB database — designed to handle a large, continuously growing catalog.

Database Architecture

Designed a MongoDB schema to store detailed keyboard specifications, nested variants, reviews, and pricing data.

3D Visualization

Integrated Three.js for interactive 3D keyboard previews, letting users rotate and examine keyboards before buying.

Data Aggregation

Built Python microservices to fetch and normalize keyboard data from multiple sources on a schedule.

Search & Filtering

Implemented multi-parameter filtering by size, switches, price, and other specs, with fast query response.

Community Features

Built user review, rating, and content submission features for the keyboard enthusiast community.

Technical Specifications

Frontend

  • React for the user interface
  • Three.js for 3D visualization
  • TailwindCSS for styling

Backend

  • Node.js and Express REST API
  • MongoDB for flexible data storage
  • Python microservices for data processing
  • JWT authentication

Database Design

  • Indexed fields for fast search
  • Aggregation pipelines for analytics
  • Automated data backups

Key Features

  • Large, continuously growing keyboard catalog
  • Advanced multi-parameter filtering
  • Interactive 3D keyboard previews
  • User reviews and community ratings

Project Highlights

Data at scale

Schema and indexing were built to keep search fast as the catalog grows, not just for the dataset size at launch.

3D without the performance hit

Lazy-loaded, progressively-upgraded 3D models keep the interactive previews smooth, including on mobile.

Self-updating by design

Scheduled Python microservices keep listings current from multiple sources with conflict resolution, without manual upkeep.