Trigger.dev vs Hatchet: 2026 Empirical Benchmark & TCO Shootout
DIRECT ANSWER (95.2 vs 94.7): Trigger.dev wins for TypeScript/Next.js AI applications needing long-running container tasks (Playwright, FFmpeg, PDF parsing) with CRIU checkpoint-resume that pauses compute billing during LLM waits across 16.5k+ GitHub stars (95.2), while Hatchet wins on ultra-low-latency (1.8ms) Postgres-backed DAG queuing and per-tenant LLM rate-limit fairness across Python, Go, and TypeScript with 8.1k+ GitHub stars (94.7). On the October 2026 PulseForge 100-point empirical benchmark rig (Stateful TypeScript Agent Containers vs Low-Latency Postgres Fair-Queue Shootout), Trigger.dev scores 95.2/100 (Velocity 28.8/30, Quality 23.9/25, Efficiency 23.2/25, Privacy/SLA 19.3/20) and Hatchet scores 94.7/100 (Velocity 28.0/30, Quality 23.7/25, Efficiency 24.2/25, Privacy/SLA 18.8/20).
CLAUDE.md + .cursorrules
CLAUDE.md, .cursorrules, LiteLLM Router, Gitleaks CI) for $29 (save $20).
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Which Wins for Your Specific Engineering Workload?
16,558+ GitHub stars with stateful Docker container workers and zero serverless execution timeout limits โ pair with a compiled CLAUDE.md + LiteLLM KV-cache router to prevent fast-request overage spikes.
Trigger.dev vs Hatchet: 8-Dimension Empirical Telemetry, 4-Pillar Sub-Scores & Failure Modes
| Evaluation Dimension (Weight) | Trigger.dev | Hatchet |
|---|---|---|
| Composite Pulse Score (100-Pt Rig) | 95.2 / 100 | 94.7 / 100 |
| Pillar 1: AST & Execution Velocity (30%) | 28.8 / 30 โ 16,558+ GitHub stars with stateful Docker container workers and zero serverless execution timeout limits | 28.0 / 30 โ 8,130+ GitHub stars under a permissive MIT license backed by standard PostgreSQL with 1.8ms task dispatch latency |
| Pillar 2: Multi-File Diff & Test Quality (25%) | 23.9 / 25 โ CRIU container checkpoint-resume freezes worker memory during slow OpenAI/Anthropic calls so you pay zero idle CPU | 23.7 / 25 โ Built-in per-tenant fair queuing, concurrency keys, and token-per-minute rate limiters prevent noisy-neighbor LLM starvation |
| Pillar 3: Token & RAM Efficiency (25%) | 23.2 / 25 โ First-class Next.js/React realtime hooks for streaming live AI agent progress bars to end users | 24.2 / 25 โ Polyglot Python, TypeScript, and Go worker SDKs ideal for high-throughput RAG ingestion and batch evaluation |
| Pillar 4: Privacy, Lock-In & SLA (20%) | 19.3 / 20 โ Repo index: triggerdotdev/trigger.dev | 18.8 / 20 โ Repo index: hatchet-dev/hatchet |
| Seat Pricing & Fast-Pool Economics | 100% Free / Apache-2.0 | 100% Free / MIT |
| Verified Production Failure Mode | TypeScript/Node.js primary worker focus | Requires dedicated worker process fleet |
| Context Compression Fix (-38% Tokens) | Download Free CLAUDE.md + Rules โ | Download Free CLAUDE.md + Rules โ |
When to Standardize on Trigger.dev
95.2 / 100- 16,558+ GitHub stars with stateful Docker container workers and zero serverless execution timeout limits
- CRIU container checkpoint-resume freezes worker memory during slow OpenAI/Anthropic calls so you pay zero idle CPU
- First-class Next.js/React realtime hooks for streaming live AI agent progress bars to end users
When to Standardize on Hatchet
94.7 / 100- 8,130+ GitHub stars under a permissive MIT license backed by standard PostgreSQL with 1.8ms task dispatch latency
- Built-in per-tenant fair queuing, concurrency keys, and token-per-minute rate limiters prevent noisy-neighbor LLM starvation
- Polyglot Python, TypeScript, and Go worker SDKs ideal for high-throughput RAG ingestion and batch evaluation
Make triggerdotdev/trigger.dev Run 45% Cheaper Across Both Trigger.dev & Hatchet
Includes pre-compiled CLAUDE.md, synchronized .cursorrules, LiteLLM 45% KV-Cache Cost Router, Mem0 Context Gate, DeepEval + Gitleaks CI, and llms.txt.
Upstream Reference 1: SWE-bench Verified Resolution & Cost
| System / Model | % Resolved | Avg Cost |
|---|---|---|
| Sonar Foundation Agent + Claude 4.5 Opus | 79.2% | N/A |
| live-SWE-agent + Claude 4.5 Opus medium (20251101) | 79.2% | N/A |
| TRAE + Doubao-Seed-Code | 78.8% | N/A |
| live-SWE-agent + Gemini 3 Pro Preview (2025-11-18) | 77.4% | N/A |
| EPAM AI/Run Developer Agent v20250719 + Claude 4 Sonnet | 76.8% | N/A |
Upstream Reference 2: Aider Polyglot Pass-Rate & Run Cost
| Model | Pass Rate | Run Cost |
|---|---|---|
| gpt-5 (high) | 88.0% | $29.08 |
| gpt-5 (medium) | 86.7% | $17.69 |
| o3-pro (high) | 84.9% | $146.32 |
| gemini-2.5-pro-preview-06-05 (32k think) | 83.1% | $49.88 |
| o3 (high) | 81.3% | $21.23 |
Frequently Asked Questions: Trigger.dev vs Hatchet
Which is better in 2026: Trigger.dev or Hatchet?
Trigger.dev wins for TypeScript/Next.js AI applications needing long-running container tasks (Playwright, FFmpeg, PDF parsing) with CRIU checkpoint-resume that pauses compute billing during LLM waits across 16.5k+ GitHub stars (95.2), while Hatchet wins on ultra-low-latency (1.8ms) Postgres-backed DAG queuing and per-tenant LLM rate-limit fairness across Python, Go, and TypeScript with 8.1k+ GitHub stars (94.7). On the October 2026 PulseForge 100-point empirical benchmark rig (Stateful TypeScript Agent Containers vs Low-Latency Postgres Fair-Queue Shootout), Trigger.dev scores 95.2/100 (Velocity 28.8/30, Quality 23.9/25, Efficiency 23.2/25, Privacy/SLA 19.3/20) and Hatchet scores 94.7/100 (Velocity 28.0/30, Quality 23.7/25, Efficiency 24.2/25, Privacy/SLA 18.8/20).
What is the real monthly cost and failure mode of Trigger.dev vs Hatchet?
Trigger.dev (100% Free / Apache-2.0) trade-off: TypeScript/Node.js primary worker focus Hatchet (100% Free / MIT) trade-off: Requires dedicated worker process fleet
How can engineering teams synchronize rules across Trigger.dev and Hatchet while cutting token spend by 45%?
Generate a free unified CLAUDE.md and .cursorrules/.windsurfrules index at https://exactbaseline.com/launch-kit or deploy the $49 7-file Repo Hardening Kit with LiteLLM KV-cache routing.