🗝️
Master Key Finance White Paper
  • Master Key Finance
  • Smart contract of Master Key Finance
  • Tokenomics
  • Truth, Trust, and Transparency
  • Project Block Oil
    • Broader blockchain ecosystem
    • Projected pricing
  • AI Sentech Memory Fields
    • Key Differentiators of Sentech Memory Fields
    • Traditional Embedding Systems
    • Graph Databases
  • Master Key Token Sales
  • MKF Revenue flow
  • BSC Utilities overview
  • Transactional Fees
  • Master Key PoRTAL
  • Soft Staking in PoRTAL
  • PoRTAL Code explanation
  • MKF High level
  • Zerosec Auditing
  • The Master Voices
Powered by GitBook
On this page
  1. AI Sentech Memory Fields

Graph Databases

PreviousTraditional Embedding SystemsNextMaster Key Token Sales

Last updated 1 month ago

Graph databases are designed to manage relational data, making them excellent for exploring complex relationships and hierarchies. However, they have notable challenges when dealing with large-scale, real-time applications:

  • Fixed Relationship Structures: Once established, relationships in graph databases are difficult to modify dynamically, making it hard to adapt to evolving data.

  • Scalability Limits: As datasets grow, performance can slow down, especially when handling millions of nodes or processing real-time queries.

  • Lack of Prioritization: Unless explicitly programmed, graph databases treat all connected nodes equally, sometimes surfacing less relevant information.

  • Complex Queries: Writing efficient queries requires specialized knowledge, making it harder for non-experts to optimize performance.

How Memory Fields Solve These Issues

Memory Fields combine the relational strengths of graph databases with real-time adaptability. They dynamically update connections, prioritize critical information, and reduce irrelevant noise. Designed for scalability, Memory Fields handle high-throughput environments efficiently, ensuring fast and context-aware data retrieval without the bottlenecks of traditional graph systems.