WJb vs Hangfire vs Quartz: Same Benchmarks, Same Machine

Background job libraries are usually compared by features.

This benchmark compares something simpler:

How fast can they enqueue work?

Repository:

https://github.com/UkrGuru/WJb.Demo/tree/main/benchmark

Benchmarks were implemented separately for:

• WJb
• Hangfire
• Quartz

Using:

• BenchmarkDotNet
• In-memory storage
• No-op jobs/actions
• Equivalent benchmark scenarios

Single Enqueue

Enqueue one job.

Result

• WJb ≈ 11× faster than Quartz
• WJb ≈ 18× faster than Hangfire

EnqueueMany (100,000 Jobs)

Bulk enqueue benchmark.

Result

• WJb ≈ 23× faster than Hangfire
• WJb ≈ 28× faster than Quartz

Parallel Enqueue (100,000 Jobs)

Multiple concurrent producers.

Memory Usage

100,000 jobs:

Result

• WJb uses ~17× less memory than Quartz
• WJb uses ~34× less memory than Hangfire

Why WJb?

WJb was designed around a very small execution model:

enqueue
  ↓
job
  ↓
action

No dashboard.

No workflow engine.

No implicit pipeline.

Just explicit background jobs.

Reproduce

Source code is included:

WJb.Benchmarks
WJb.Benchmarks.Hangfire
WJb.Benchmarks.Quartz

Run:

dotnet run -c Release

Final Numbers

For these benchmark scenarios:

✅ Fastest enqueue: WJb

✅ Fastest bulk enqueue: WJb

✅ Fastest parallel enqueue: WJb

✅ Lowest memory usage: WJb

Benchmark scenarios are intentionally small, reproducible, and focused on enqueue performance.
Additional scenarios will be added only when equivalent implementations exist for all compared libraries.