FlatSignals

FlatSignals is an ultra-fast reactivity library (~0.5 KB) optimized for high-frequency, few-to-many updates.

🚀 Why it’s fast:

• No graph traversals
• O(1) dynamic dependency management
• Lazy computations by default

Benchmarks

Note: Benchmarks were run in a controlled environment. Results may vary based on hardware and JavaScript engine. You can reproduce these benchmarks by cloning the repo and running pnpm bench.

1-to-64 fanout

Library	Operations/sec ⚡	vs flatsignals
flatsignals 🏆	449,848	baseline
alien-signals	261,082	1.72x slower
@preact/signals	230,899	1.95x slower
@reactively/core	182,403	2.47x slower
@vue/reactivity	152,709	2.95x slower
@maverick-js/signals	137,712	3.27x slower
Angular Signals	98,597	4.56x slower
@solidjs/signals	78,849	5.71x slower

High-frequency updates

Library	Operations/sec ⚡	vs flatsignals
flatsignals 🏆	976,139	baseline
alien-signals	502,513	1.94x slower
@preact/signals	492,543	1.98x slower
@reactively/core	438,882	2.22x slower
@maverick-js/signals	343,368	2.84x slower
Angular Signals	241,189	4.05x slower
@vue/reactivity	221,537	4.41x slower
@solidjs/signals	202,492	4.82x slower

Diamond

Library	Operations/sec ⚡	vs flatsignals
flatsignals 🏆	4,556,987	baseline
alien-signals	3,028,320	1.50x slower
@preact/signals	2,531,788	1.80x slower
@reactively/core	1,688,053	2.70x slower
Angular Signals	1,614,432	2.82x slower
@vue/reactivity	1,563,865	2.91x slower
@maverick-js/signals	1,407,975	3.24x slower
@solidjs/signals	870,080	5.24x slower

Installation

# npm
npm install flatsignals

# pnpm
pnpm add flatsignals

# yarn
yarn add flatsignals

Usage

import { signal, computed, effect } from "flatsignals";

const counter = signal(0);
const double = computed(() => counter.val * 2);
const log = effect(() => console.log(double.val));

With React

import { useFlatSignal, useFlatReader } from "flatsignals/react";
import { counter, double } from "./signals";

function MyCounter() {
  const [val, setVal] = useFlatSignal(counter);
  return <button onClick={() => setVal(val + 1)}>Count: {val}</button>;
}

function ReadDouble() {
  const val = useFlatReader(double);
  return <div>{val}</div>;
}

Use Case

Best suited for: Scenarios with a small number of reactive signals driving many dependent computations.

Limitations:

• Signal limit: Maximum of 32 signals per root. Beyond this limit, effects may trigger even when their tracked signals haven't changed.
• Set complexity: O(N) time proportional to dependent computations (amortized through batching)
• Eager propagation: All downstream nodes marked dirty immediately, even when intermediate values unchanged