Since their Show HN a few months ago, they have addressed common feedback including built-in support for fanout workflows, support for HTTP-based triggers, and their RabbitMQ dependency. They have also launched more features like support for global rate limiting, steps which only run on workflow failure, and custom event streaming. They believe that PostgreSQL is the right choice for a task queue due to its ease of use and ability to model higher-order concepts.
Key takeaways:
- Hatchet is a modern task queue being developed as an alternative to tools like Celery for Python and BullMQ for Node, with a focus on using PostgreSQL for task queuing.
- They have launched a self-serve cloud platform, allowing anyone to create tasks on their platform, and have also provided a demo for users to try out.
- They have addressed common feedback from their initial launch, including adding built-in support for fanout workflows, support for HTTP-based triggers, and the launch of hatchet-lite which bundles various Hatchet components in a single Docker image.
- Hatchet is being used for a variety of use-cases, including orchestrating RAG pipelines, queueing user notifications, building agentic LLM workflows, and scheduling image generation tasks on GPUs.