Unibase Docs
  • Introduction
    • Architecture
    • Core Components
    • Quick Start
  • Membase
    • 📚Architecture
    • Identity
    • Multi Memory
    • Authorization
    • 🚀Quick Start
  • AIP
    • Design
    • Agent Interaction Process
    • Implementation
    • Quick Start
      • Tool
      • Agent
        • Agent-Tool Interaction Via gRPC
        • Agent-Tool Interaction Via SSE
        • Agent-Agent Interaction
      • Chess game
  • Unibase DA
    • DA
    • Storage
    • Quick Start
      • Nodes boostrap
        • Storage Node
        • Validator Node
        • Stream Node
        • Docker
      • Nodes operations
  • Developers
    • Hub
    • SDK
    • API Reference
  • Alpha Testing
    • Testing plan
    • Requirements
    • Chains
  • 🚀Examples
Powered by GitBook
On this page
  • 💡 Why It Matters
  • 🔑 Core Capabilities
  • 🧩 Architecture Highlights
  • 📌 Summary
  1. Unibase DA

Storage

The AI Native Storage Layer is purpose-built to meet the intensive storage demands of AI agents and models in a decentralized environment. Traditional Web3 storage systems fall short when it comes to high-throughput, large-scale, programmable, and value-driven AI data workflows. Unibase Storage solves this with a robust, scalable, and intelligent storage layer.

💡 Why It Matters

AI services require real-time access to massive amounts of data. Whether it’s context windows, model parameters, or long-term memory, delays in storage or retrieval significantly hinder AI performance. The AI Native Storage Layer is optimized for this reality.

🔑 Core Capabilities

⚡ 1. High-Performance Data Access

  • Optimized for AI inference and training workloads.

  • Supports low-latency and high-throughput data read/write (up to 100GB/s).

  • Seamlessly connects to Unibase DA for verifiable, on-chain-accessible storage operations.

Perfect for AI Agents requiring real-time context loading and memory updates.

♾️ 2. Massive Scalability & Private Pools

  • Handles exabyte-scale (EB+) data volumes.

  • Horizontally scalable to millions of storage nodes.

  • Supports private storage pools for dedicated applications or enterprise use.

Offers flexibility for both public decentralized networks and custom enterprise deployments.

⚙️ 3. Programmability & Ownership Control

  • Fully programmable via smart contracts.

  • Customizable access control, lifecycle rules, and data governance.

  • Allows users or apps to define storage logic (e.g. auto-expiry, pricing, access triggers).

Empowers developers with fine-grained data logic tailored to AI workflows.

💰 4. Native Data Assetization

  • Treats stored data as on-chain assets.

  • Enables tokenization, trading, and monetization of data.

  • Compatible with DeFi, marketplace, and compute-to-data paradigms.

Transforms data from passive storage into active economic value.

🧩 Architecture Highlights

  • Built atop Unibase DA for tamper-proof DA + storage validation.

  • Compatible with zk verification, smart contract hooks, and programmable storage lifecycle.

  • Designed to work with Membase and AIP for seamless AI agent memory management.

📌 Summary

Unibase's AI Native Storage Layer enables decentralized AI applications to scale intelligently with:

  • ✅ Real-time, high-speed data access

  • ✅ Massive and elastic storage capacity

  • ✅ Programmable ownership and access logic

  • ✅ Monetizable, verifiable data assets

It’s not just storage — it’s intelligent, sovereign memory infrastructure for Web3 AI.

PreviousDANextQuick Start

Last updated 7 days ago