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AI visibility report

Hatchet ranks #11 in Workflow Orchestration & Durable Execution AI search.

Outside the top three on 25 of the 25 prompts buyers actually ask.

Temporal is cited on 22 of those losses.

25 prompts
6 platforms
Updated Aug 13, 2026 - refreshed weekly
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4percent
Presence Rate
Low presence

#11 among 11 vendors · still absent from 96% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

+0.75
Sentiment
-1.00.0+1.0
Very positive
#11of 11

Peer Ranking

#1#11
Below averagein Workflow Orchestration & Durable Execution

Key Metrics

Presence Rate4.0%
Share of Voice1.4%
Avg Position#28.0
Docs Presence1.3%
Blog Presence0.7%
Brand Mentions6.7%

Platform Breakdown

ChatGPT
16%4/25 prompts
Perplexity
4%1/25 prompts
Grok
4%1/25 prompts
Google AI Mode
0%0/25 prompts
Bing Copilot
0%0/25 prompts
Gemini Search
0%0/25 prompts

Narrower footprint, stronger tone. Hatchet ranks #11 on presence but #1 on sentiment. That means the brand is framed well when it appears, but still needs broader prompt-response coverage.

Where Hatchet is losing

Prompts where competitors are visible and Hatchet is not.

These prompt-level losses are the first prompts to track and repair.

Where Hatchet is winning

No clear strengths identified yet.

Where Hatchet is losing5

  • What durable execution tools guarantee at-least-once execution and idempotency so workflows never silently drop work in a distributed system?

    Competitors on 6 platforms

    Track this prompt
  • What durable workflow platforms support scheduling and cron-like triggers natively so teams can replace job schedulers without adding another tool?

    Competitors on 5 platforms

    Track this prompt
  • What durable execution tools work well with serverless compute platforms so individual workflow steps run as isolated functions without dedicated workers?

    Competitors on 5 platforms

    Track this prompt
  • What workflow orchestration tools support human-in-the-loop workflows where execution pauses indefinitely until a person approves the next step?

    Competitors on 5 platforms

    Track this prompt
  • Which workflow orchestration platforms let developers write workflows in plain code without learning a proprietary DSL or YAML configuration?

    Competitors on 5 platforms

    Track this prompt

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Research dossierCapabilities, use cases, sources, reviews, pricing, and FAQ

Overview

Hatchet is an open-source, developer-first workflow orchestration and durable execution platform built on PostgreSQL. Founded in 2023 and backed by Y Combinator (W24), it provides engineering teams with a unified platform for running background tasks, orchestrating AI agents, and executing mission-critical workflows at scale. Hatchet bundles a durable task queue, DAG-based workflow engine, real-time observability dashboard, alerting, and multi-language SDKs (Python, TypeScript, Go, Ruby) into a single deployable service. Workers run on customer infrastructure while the orchestration engine is available as Hatchet Cloud or as a fully self-hosted deployment requiring only Postgres. The platform processes billions of tasks per month and claims over 100 million tasks per day for AI-first companies.

Hatchet is a durable workflow orchestration engine and background task platform built on Postgres. It enables developers to define tasks and workflows as code, execute them with fault tolerance and automatic retries, and observe them through a real-time dashboard. It is available as a managed cloud service or a self-hosted open-source deployment.

Key Facts

Founded
2023
HQ
San Francisco, CA / New York, NY, USA
Founders
Alexander Belanger, Gabriel Ruttner
Employees
1-10
Funding
~$5.7M
Customers
Thousands of engineers; hundreds of comp
Status
Private

Target users

Application engineers and backend developers at fast-growing startupsAI/ML engineering teams building agentic and LLM-powered applicationsPlatform and infrastructure engineers managing distributed background job systemsDevOps and SRE teams requiring durable, observable task executionCompanies processing large-scale document, data, or media workloadsEngineering teams migrating off Celery, BullMQ, or Sidekiq to a more observable platform

Key Capabilities10

  • Durable task queue built on PostgreSQL with exactly-once semantics and persistent event log
  • DAG-based workflow orchestration with automatic parent-to-child output routing
  • Durable execution with automatic checkpointing, replay, and resumption after failure
  • Per-user/per-tenant concurrency control and rate limiting with Group Round Robin fairness
  • Cron scheduling, one-time future scheduling, and durable sleep
  • Real-time web dashboard with workflow visualization, logging, and alerting
  • Multi-language SDKs: Python, TypeScript, Go, Ruby
  • Auto-retry with configurable retry policies and timeout handling
  • Event-driven triggers and human-in-the-loop signaling (event waits)
  • Self-hostable with minimal infra (Postgres only); 100% MIT-licensed open source

Key Use Cases8

  • AI agent orchestration with durable state and guardrails
  • Massive parallel document ingestion and indexing pipelines (RAG, vector DB updates)
  • Background task management replacing Celery, BullMQ, or Sidekiq
  • Multi-tenant SaaS workload fairness and rate limiting
  • GPU job scheduling and batching
  • Long-running mission-critical workflows requiring fault tolerance
  • Event-driven microservice coordination
  • Cron-based data pipelines and scheduled batch processing

Hatchet customer outcomes

Greptile

50% reduction in failed runs

Adopted Hatchet to scale codebase indexing workflows with improved durability and visibility. Failed workflow runs were reduced by 50% and the team doubled their user base in two weeks after switching.

Aevy

Processing time cut from ~1 week to <1 hour for 50,000 documents

Used Hatchet to orchestrate parallel AI document processing for critical infrastructure (solar and wind farms). Processing time for large asset document sets was cut from nearly a week to under one hour.

Recent Trend

Visibility+2.4 pts
Avg position+2.70
Sentiment+0.33

How AI describes Hatchet3

...tgpt.com) | Yes — cron schedules | Yes; retries, checkpoint/resume | TypeScript-heavy application teams | Yes | | Hatchet | Yes — cron + one-time schedules | Yes, including durable sleep | OSS ba...

What durable workflow platforms support scheduling and cron-like triggers natively so teams can replace job schedulers without adding another tool?

chatgpt-searchDirect Hatchet mention
...Yes | Horizontally scaled servers + independently scalable workers | Strong for task/DAG-style orchestration | | Hatchet | Potentially, but less independently demonstrated at the million-open-workflow level | Distributed task scheduling with...

Which workflow orchestration platforms can scale to millions of concurrent workflow executions without degrading scheduler throughput?

chatgpt-searchDirect Hatchet mention
Hatchet — interesting middle ground Hatchethatchet.run provides durable tasks, retries, scheduling, event triggers, concurrency controls and workflow orchestration.

What workflow orchestration tools do platform teams recommend for reducing the custom infrastructure a product team needs to build for reliable background jobs?

chatgpt-searchDirect Hatchet mention

Alternatives in Workflow Orchestration & Durable Execution6

Hatchet positions itself as a developer-first, code-native orchestration engine that unifies durable task queues, DAG-based workflow orchestration, and AI agent orchestration into a single Postgres-backed platform.

  • Unlike Temporal, which is narrowly focused on durable execution with support for multiple database backends, Hatchet covers a wider array of use-cases including multiple queueing strategies, rate limiting, DAG features, conditional triggering, and streaming.
  • Compared to DAG-centric data platforms like Prefect or Airflow, Hatchet targets application engineers rather than data engineers, emphasizing low latency (<20ms task start), high throughput, and tight SDK integration.
  • It differentiates from library-based queues (Celery, BullMQ) through persistent observability and a built-in real-time dashboard.
  • Its 100% MIT-licensed open-source codebase and minimal infrastructure requirements (Postgres only) are a deliberate self-hosting advantage.
View category comparison hub

Reviews

Praised

  • Code-first, language-native SDK design
  • Simple self-hosting with Postgres only
  • Real-time dashboard visibility and DAG visualization
  • Strong durability and automatic retry behavior
  • Low task start latency (<20ms)
  • Responsive founders and community support via Discord
  • MIT open-source license with feature parity to cloud

Criticized

  • Small team limits enterprise support capacity
  • Data retention windows are tier-gated (short on lower plans)
  • Not ideal for very high throughput (>10k/s) without retention
  • Limited to Postgres backend (no Cassandra/MySQL alternative)
  • Fewer native data connector integrations vs. data-platform competitors

No aggregate review data from platforms such as G2 or Gartner Peer Insights was found for Hatchet at time of research. Qualitative sentiment from the developer community (GitHub, Discord, Hacker News) is generally positive, noting ease of setup, code-first developer experience, and strong observability features. Customer testimonials highlight significant reductions in failed runs and dramatic processing time improvements.

Pricing

Hatchet Cloud offers four tiers: Developer (free + $10/1M task runs after first 100K included); Team ($500/month + usage, 10 users, 3-day retention, 500 RPS); Scale ($1,000/month + usage, unlimited users, 7-day retention, HIPAA/audit logs); Enterprise (custom, with latency guarantees, SSO/SAML, bring-your-own-cloud, dedicated support). Annual billing saves 20%. The open-source self-hosted version is 100% MIT-licensed and free.

Limitations

  • Hatchet targets throughput up to ~10k tasks/second with retention; the GitHub README notes that library-based queues like BullMQ/Celery may be preferable for >10k/s workloads without retention requirements.
  • Data retention windows are tier-gated (no retention on free, 3 days on Team, 7 days on Scale).
  • The platform does not natively support non-Postgres result stores (unlike Temporal which supports Cassandra, MySQL, SQLite).
  • As a small, early-stage startup (~6 employees), long-term enterprise support capacity and feature velocity relative to larger vendors is a consideration.
  • No publicly verifiable G2/analyst review data was found at research time.

Frequently asked questions

Topic coverageCoverage by buyer topic

Topic Coverage

Capability1/5DevEx2/5Integrations &Ecosystem1/5Performance &Reliability2/5Setup & First Run0/5

Prompt-Level Results

Brand citedCompetitor citedNot cited
PromptGoogle AI ModePerplexityBing CopilotChatGPTGemini SearchGrok
Capability1/5 cited (20%)

I need a workflow engine that supports saga patterns for distributed transactions with automatic compensation on failure — what are my options?

Which durable workflow platforms support versioning workflows so you can deploy code changes without breaking in-flight executions?

What workflow orchestration tools support human-in-the-loop workflows where execution pauses indefinitely until a person approves the next step?

Which platforms handle long-running workflows that can sleep for days or months and resume exactly where they left off after an external event?

Which durable execution platforms handle fan-out scenarios where a parent workflow spawns thousands of child tasks and waits for all results?

Developer Experience2/5 cited (40%)

What workflow orchestration tools do platform teams recommend for reducing the custom infrastructure a product team needs to build for reliable background jobs?

Which durable workflow platforms support TypeScript-native workflows with strong type safety and IDE autocomplete?

What durable execution tools have the best local development experience so engineers can step through a long-running workflow without deploying to a staging environment?

Looking for a workflow orchestration platform with a visual workflow replay UI so on-call engineers can debug a failed run without reading raw logs — what are my options?

Which workflow orchestration platforms let developers write workflows in plain code without learning a proprietary DSL or YAML configuration?

Integrations & Ecosystem1/5 cited (20%)

What durable workflow platforms support scheduling and cron-like triggers natively so teams can replace job schedulers without adding another tool?

What durable execution tools work well with serverless compute platforms so individual workflow steps run as isolated functions without dedicated workers?

Looking for a workflow platform with strong LLM provider integrations for building AI agent pipelines with retry logic and state persistence — what should I look at?

Which workflow orchestration tools integrate with observability platforms so traces span across workflow steps and external API calls?

Which workflow orchestration platforms integrate natively with event streaming platforms to trigger workflows from topic messages?

Performance & Reliability2/5 cited (40%)

Which workflow orchestration platforms can scale to millions of concurrent workflow executions without degrading scheduler throughput?

What durable execution tools guarantee at-least-once execution and idempotency so workflows never silently drop work in a distributed system?

Which durable workflow platforms handle partial outages gracefully by resuming in-progress executions automatically when the system recovers?

Which workflow platforms have the lowest latency for triggering a new workflow execution in response to an inbound webhook event?

What orchestration tools are battle-tested for production use at high scale — which ones do high-growth startups rely on for mission-critical workflows?

Setup & First Run0/5 cited (0%)

What workflow orchestration platforms offer a managed cloud service with minimal ops overhead for a 10-person backend team?

I'm evaluating durable execution platforms for a startup with complex multi-step background jobs — which ones have the fastest time to value?

What's the easiest durable workflow platform to adopt for a backend team tired of managing unreliable cron jobs and retry logic from scratch?

Which durable workflow tools have self-hosted options that are straightforward to deploy on a single server for a team not ready for managed services?

Which workflow orchestration tools can a Node.js team integrate into an existing codebase without rewriting their business logic?

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Vertical Ranking

#BrandPres.SoVDocsBlogMent.PosSentiment
1Temporal41.3%35.7%22.0%16.7%1.3%#20.3+0.43
2Inngest21.3%14.4%14.0%6.7%47.3%#26.8+0.49
3Restate19.3%9.2%12.0%4.0%32.0%#22.2+0.49
4AWS Step Functions17.3%8.6%5.3%0.0%0.0%#24.1+0.58
5Kestra14.0%5.8%4.7%2.7%13.3%#28.7+0.38
6Prefect11.3%6.7%4.7%5.3%0.0%#30.4+0.43
7Trigger.dev10.0%6.7%2.7%1.3%23.3%#35.3+0.38
8Orkes8.0%3.7%1.3%5.3%13.3%#25.1+0.45
9Windmill6.7%3.4%0.0%4.0%0.0%#16.6+0.39
10Camunda6.7%4.3%3.3%5.3%21.3%#58.4+0.41
11Hatchet4.0%1.4%1.3%0.7%6.7%#28.0+0.75

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