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Performance Benchmarks

Real-world performance metrics showing djust's Rust-powered advantages over competing frameworks.

0.8ms
Template Rendering
10,000 renders avg
<100μs
VDOM Diffing
Typical component
~29KB
Client Bundle
Minified + gzip
10,000+
Concurrent Users
Single server

Template Rendering Speed

Rendering 10,000 iterations of a typical dashboard template (200 LOC, 15 variables, 3 loops). Lower is better.

djust (Rust)
0.8ms avg
LiveView (Elixir)
1.5ms avg
Livewire (PHP)
7.2ms avg
Django (Python)
12.5ms avg

VDOM Diffing Performance

Time to diff and generate patches for a complex component (100 DOM nodes, 20% change rate). Lower is better.

djust (Rust)
87μs avg
LiveView (Elixir)
210μs avg
Livewire (PHP)
480μs avg

Client Bundle Size

Minified and gzipped JavaScript sent to the client. Smaller bundles mean faster initial page loads.

djust
~29 KB
HTMX
~14 KB
LiveView
~30 KB
Livewire
~50 KB

Server Memory Usage

Memory usage per concurrent WebSocket connection. Lower is better for scaling.

djust (Rust VDOM)
~2.5 KB/conn
LiveView (BEAM)
~3.8 KB/conn
Livewire (HTTP)
N/A (polling)

Request Throughput

Requests per second handled on a single server (4 cores, 8GB RAM). Higher is better.

djust
~12,500 req/s
LiveView
~11,000 req/s
Livewire
~3,200 req/s
HTMX
~8,500 req/s

Methodology

Test Environment

  • • AWS EC2 c5.xlarge (4 vCPUs, 8GB RAM)
  • • Ubuntu 22.04 LTS
  • • Python 3.11, Elixir 1.15, PHP 8.2
  • • PostgreSQL 15 (localhost)

Benchmarking Tools

  • wrk2 for HTTP load testing
  • hyperfine for command-line benchmarks
  • criterion for Rust microbenchmarks
  • • Custom WebSocket load tester (10,000 concurrent connections)

Test Application

  • • Real-time dashboard with 15 widgets
  • • Updates every 2 seconds via WebSocket
  • • PostgreSQL queries (5 simple, 2 joins)
  • • ~200 LOC template, ~100 DOM nodes

Reproducibility

All benchmarks are open source and reproducible. See our benchmarks repository for full details.

Experience the Performance Yourself

See djust's speed in action. Explore examples or run benchmarks locally.