Hatchet

Limitations

• High-volume PostgreSQL queue pressure: under sudden bursts of tens of thousands of tasks, the default PostgreSQL message queue can saturate database connections and trigger API crashes, requiring teams to add a dedicated PgBouncer pool or configure an optional RabbitMQ broker for high throughput.
• Persistent gRPC connection overhead: workers maintain long-lived bidirectional gRPC streams to the engine, which complicates load balancing across corporate proxies or serverless runtimes that drop idle connections.
• Operational database growth: storing complete run histories and step outputs expands PostgreSQL tables quickly, making regular partition cleanup and retention policies mandatory.
• Slot allocation edge cases: ungraceful worker shutdowns or network splits can delay capacity slot releases, requiring explicit heartbeat and timeout configuration.

Who should use it

• DevOps engineers running private cloud or on-premises infrastructure who require durable background task execution without sending payloads to hosted cloud queues.
• Backend teams building multi-step AI agent workflows that need durable sleep and step-by-step state recovery across long-running model calls.
• Platform teams replacing legacy cron jobs or Celery clusters who want unified DAG scheduling, worker affinity, and execution tracing across microservices.

FAQ

Is Hatchet free for commercial use? Yes. Hatchet is distributed under the MIT license, allowing organizations to self-host and run it in commercial environments without license fees.

Hatchet vs Amazon SQS — which should you choose? Choose Amazon SQS when you need zero-maintenance serverless message queuing native to AWS. Choose Hatchet when you need durable multi-step workflows, execution visibility, and total control over data residency in your own database.

Can you self-host Hatchet without RabbitMQ? Yes. Hatchet runs out of the box using PostgreSQL as both its message queue and state store, with RabbitMQ remaining an optional add-on for high-throughput burst workloads.

Verdict

Hatchet is an ideal fit when your engineering team needs durable task orchestration and strict data sovereignty without the operational complexity of enterprise workflow platforms or the vendor lock-in of proprietary cloud queues. Sustained development activity with commits throughout late 2026 and a permissive MIT license make it straightforward to adopt in enterprise architectures, provided your team has the operational capacity to manage and tune PostgreSQL under write-heavy workloads.