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KotaDB Planning Overview

This directory contains comprehensive planning documents for KotaDB, a custom database designed for distributed human-AI cognition.

Planning Documents

  1. IMPLEMENTATION_PLAN.md - Complete 13-week implementation roadmap
  2. TECHNICAL_ARCHITECTURE.md - Detailed system architecture and design
  3. DATA_MODEL_SPECIFICATION.md - Storage formats, index structures, and compression schemes
  4. QUERY_LANGUAGE_DESIGN.md - KQL (KOTA Query Language) specification
  5. MVP_SPECIFICATION.md - 3-week MVP plan for immediate value

Key Decisions

  • Storage: Keep markdown files as source of truth, database stores metadata/indices only
  • Architecture: Hybrid document/graph/vector database optimized for cognitive workloads
  • Query Language: Natural language first with structured fallback
  • Implementation: MVP in 3 weeks, full system in 13 weeks

Background

This project emerged from recognizing that narrative-based memory systems are fundamentally flawed for AI. Instead, KotaDB implements a dynamic model with:

  • Documents as nodes in a knowledge graph
  • Time as a first-class dimension
  • Semantic understanding built-in
  • Human-readable storage always maintained

Created as part of the KOTA (Knowledge-Oriented Thinking Assistant) project.