01

THE REAL-TIME ENGINE
BEYOND SPEED.

Zero latency. No overhead. Build and deploy hyper-scale data pipelines directly from your terminal. Write TypeScript. Run anywhere.

npx duckfacts launch system-demo
Duckfacts Preview

$ npx duckfacts launch system-demo

[info] Initializing Duckfacts concept preview...

[ok] Cluster connected. 64 nodes ready.

RECEIVE: packet_id=99283 type=PROTOBUF size=12.4kb

PROCESS: pipeline=enrich_telemetry duration=0.12ms

EMIT: target=websocket_farm throughput=8.2GB/s

SYNC: global_state_db created (8ms)

METRIC: CPU 8% | RAM 124MB

INBOUND: 1.2M req/s from us-east-1

RELOAD: telemetry_v3 injected successfully

_

02

Features

01

Ultra-Low Latency

Sub-millisecond processing. Native Rust core with JavaScript bindings for maximum developer velocity without performance trade-offs.

02

Zero Config Deploy

Deploy to any cloud provider or bare metal with a single command. Automated scaling and health management built-in.

03

Native Connectors

Direct integration with Kafka, Redis, Postgres, and WebSockets. No middleman, no translation layer.

04

State is JSON

Game-engine inspired state management. Snapshot and restore data clusters instantly. Multiplayer-grade synchronization.

05

Hot Pipeline Reload

Update your logic in real-time without dropping packets. Our VM swaps instruction sets in nanoseconds.

06

Visual Debugging

Inspect every packet flow through a real-time visual UI. This Duckfacts concept focuses on speed, control, and visual clarity.

03

Duckfacts vs Legacy

Metric Duckfacts Kafka Spark Streaming RabbitMQ
End-to-End Latency < 1ms 10-50ms 100ms+ 2-5ms
Setup Complexity Zero High (Zk/Quorum) Extreme Medium
Throughput / Node 8.2 GB/s ~800 MB/s ~1.2 GB/s ~400 MB/s
Resource Usage Minimal Heavy JVM Massive Cluster Medium Erlang
Programming Model JS/TS Pipelines Java/Scala/DSL Scala/Python Protocol-based
04

Complete Pipeline in 20 Lines

pipeline.ts 
import { Engine } from "@duckfacts/system-core";

// Initialize cluster node
const app = new Engine({ port: 8080 });

// Define real-time processing stream
app.stream("raw-clicks")
  .filter(data => data.value > 100)
  .map(async (data) => {
    const user = await app.state.get(`user:${data.id}`);
    return { ...data, country: user.geo };
  })
  .window({ size: "10s", slide: "1s" })
  .emit("processed-events");

// Launch the experience
app.run();

Get Started

# install

npm install -g duckfacts-launch

# create

duck init my-stream

# deploy

duck ship

Duckfacts handles the visual system, rhythm, and interface clarity so the message lands fast and feels premium.

DUCK

Ready to ship faster?

Join 10,000+ developers building the future of real-time apps.