A durable background task queue and workflow orchestration platform built on Postgres with observability and flow control.
Hatchet is a comprehensive platform for running background tasks and durable workflows at scale. It bundles a durable task queue, observability, alerting, a real-time dashboard, and a CLI into a single solution, designed to handle complex task orchestration beyond simple FIFO queues.
Developers and engineering teams building applications that require reliable background job processing, complex workflow orchestration, and enhanced observability beyond basic task queues. This includes those transitioning from libraries like Celery or BullMQ who need more control and durability.
Developers choose Hatchet because it provides a unified, self-hostable platform with built-in durability, observability, and advanced orchestration features like DAGs, flow control, and event triggers, reducing the need to assemble and maintain multiple disparate tools.
🪓 Run Background Tasks at Scale
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Hatchet persists every task execution in Postgres, enabling detailed monitoring and debugging, and ensuring no work is lost during failures, as emphasized in its durable task queue feature.
Supports DAGs, event triggers, and durable tasks, allowing developers to build complex, multi-step workflows beyond simple FIFO queues, with examples provided in the task orchestration section.
Comes with a real-time dashboard, built-in logging, and alerting (Slack/email), reducing the need for external monitoring setups and providing immediate visibility into task performance.
Offers dynamic concurrency limits and rate limiting based on user or tenant keys, helping to prevent system overloads and improve stability, as demonstrated in the flow control examples.
Hatchet is tightly coupled to Postgres for storage, unlike competitors like Temporal that support multiple databases, which can be a limitation for teams with different database preferences or constraints.
As a standalone service requiring Docker and server management, it adds deployment and maintenance overhead compared to library-based solutions like Celery that integrate directly into application code.
For use cases prioritizing raw speed over durability, such as high-volume event processing without retention, Hatchet may be less efficient than dedicated task queues like BullMQ, as acknowledged in the comparisons.
hatchet is an open-source alternative to the following products:
Prefect is a workflow orchestration platform for data engineering, enabling developers to build, schedule, and monitor dynamic data pipelines with Python.
Celery is a distributed task queue system for Python that handles asynchronous job processing, scheduling, and message passing, often used with web frameworks like Django.
Temporal is an open-source workflow orchestration platform that enables developers to build and run reliable applications using durable execution.
Apache Airflow is an open-source platform for programmatically authoring, scheduling, and monitoring workflows through directed acyclic graphs (DAGs).
BullMQ is a Node.js library for handling jobs and messages with Redis, built on top of Bull, offering improved performance and additional features for queue management.
Dagster is a data orchestrator for machine learning, analytics, and ETL pipelines, focusing on development productivity, operational robustness, and observability.