Hatchet
Hatchet is a distributed workflow orchestrator designed for building resilient and scalable data pipelines, particularly for AI agents and context engineering.
Our verdict
Who it's for
Run fast and reliable data pipelines for context engineering and AI agents.
Who should look elsewhere
Specific pricing details for additional usage are not fully transparent on the pricing page for all tiers.
Pros
- +Significantly reduces failed runs and improves reliability for data pipelines.
- +Enables efficient processing of large datasets and parallel execution.
- +Simplifies complex AI agent orchestration and state management.
- +Offers flexible deployment options (managed or self-hosted).
- +Code-first approach promotes maintainability and testability.
Cons
- −Specific pricing details for additional usage are not fully transparent on the pricing page for all tiers.
- −Requires some technical expertise to integrate and deploy workers.
- −Advanced features like custom SLAs and compliance (SOC 2, HIPAA, BAA) are only available on the Enterprise plan.
Key features
- ✓Low-latency, high-throughput task execution (<20ms start times)
- ✓Durable logging of task invocations with checkpoint recovery
- ✓Code-first SDKs for Python, TypeScript, and Go
- ✓Automatic retries and intelligent rate limiting
- ✓Exactly-once semantics for updating vector databases
- ✓Built-in orchestration primitives for AI agents (tool calls, timeouts, state management)
- ✓Eventing for human-in-the-loop signaling and streaming responses
- ✓Fan-out to thousands of workers with single function calls
Pricing
| Plan | Price | Billing | Notes |
|---|---|---|---|
| Free | $0 | month | For testing and small-scale experimentation; Task Runs: 10/s; Concurrent Runs: 2k |
| Starter | $180 | month | For smaller systems starting to face scaling challenges; Task Runs: 100/s; Concurrent Runs: 10k |
| Growth | $425 | month | For larger services experiencing especially tricky scaling problems.; Task Runs: 500/s; Concurrent Runs: 100k |
| Enterprise | — | month | For especially complex systems with unique requirements.; Task Runs: 500-10k/s; Concurrent Runs: 100k-1M |