⚡ HyperSync Engine

Next-generation reactive data synchronizer built with distributed consensus and zero-overhead memory layouts.

License: MIT Build Status Coverage Version

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🌟 Key Features

• 🚀 Sub-millisecond Latency: Microsecond deterministic consensus pipelining
• 🔒 End-to-End Encryption: Authenticated AES-256-GCM transport layer
• 📊 Dynamic Topology: Automatic mesh failover & peer discovery
• 🌐 Universal Runtime: Runs seamlessly on Node.js, Bun, Edge Workers, and Browsers

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📐 Architecture Overview

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⚡ Quick Start

Installation

bashCopy
# Install via package manager
pnpm add @hypersync/engine
# or using bun
bun add @hypersync/engine

Basic Usage

typescriptCopy
import { createCluster, MessageEnvelope } from "@hypersync/engine";

const cluster = await createCluster({
  nodes: ["node-1.region.internal:8080", "node-2.region.internal:8080"],
  heartbeatMs: 250,
  maxBatchSize: 10_000,
});

cluster.on("commit", (envelope: MessageEnvelope) => {
  console.log(`[HyperSync] Committed batch #${envelope.batchId} in ${envelope.latencyMs}ms`);
});

await cluster.publish("telemetry.global", {
  timestamp: Date.now(),
  metric: "cpu_usage",
  value: 42.8,
});

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🔬 Mathematical Performance Model

The throughput scaling curve $\mathcal{T}(n, k)$ as a function of cluster nodes $n$ and concurrency factor $k$ follows:

$$\mathcal{T}(n, k) = \frac{k \cdot \mu}{\log_2(n) + \alpha \cdot \sqrt{k}} \times \left( 1 - e^{-\lambda / \sigma} \right)$$

Where:

• $\mu$ is single-node memory bandwidth ($10^6$ ops/sec)
• $\alpha$ represents network jitter coefficient ($0.04$)
• $\sigma$ represents queue saturation threshold

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💡 Important Notices

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📊 Benchmark Comparison

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📋 Roadmap & Checklists

• v3.0: Zero-allocation memory parser
• v3.5: Raft distributed consensus overhaul
• v3.8: WebAssembly runtime driver
• v4.0: Quantum-resistant Kyber encryption envelope
• v4.2: Direct NVMe kernel bypass support