DBOS Python 1.0 – Lightweight Durable Workflows Built on Postgres
Hi HN – this is Peter from DBOS here with Qian (qianli_cs) and Jeremy (jedberg). We’re building an open-source, lightweight durable workflows library on top of Postgres. Ever since we first launched on HN last year, we’ve been blown away by the support, feedback, and response we’ve received from the community. We've realized durable workflows are critical for everything from business processes to AI automation to data pipelines, but most existing durable orchestration tools are either too heavy or too complicated for most applications. Instead, we're building something lightweight, simple,…
What it does
In the maker’s words, at launch
Hi HN – this is Peter from DBOS here with Qian (qianli_cs) and Jeremy (jedberg). We’re building an open-source, lightweight durable workflows library on top of Postgres. Ever since we first launched on HN last year, we’ve been blown away by the support, feedback, and response we’ve received from the community. We've realized durable workflows are critical for everything from business processes to AI automation to data pipelines, but most existing durable orchestration tools are either too heavy or too complicated for most applications. Instead, we're building something lightweight, simple, and easy to drop into any existing app. The core of DBOS is durable Postgres-backed workflows. The library checkpoints the state of your program (which workflows are running, what steps have completed) directly in Postgres. If your program fails, when it restarts your workflows use these checkpoints to automatically recover from the last completed step. What we really love about DBOS is how lightweight it is–you don’t need to deploy a separate workflow orchestrator or manage new workers, just install this open-source library, connect it to Postgres, and annotate workflows and steps in your program to make them durable. Today, we’re releasing DBOS Python 1.0. This enhances workflows with many powerful features we’ve been building over the last few months, including: - Durable queues. Postgres-backed queues with all the queuing features of BullMQ/Celery (concurrency limits, rate limits, timeouts, priority, deduplication, etc.). Plus, they integrate with durable workflows, so you can write a workflow that enqueues 1K tasks, waits for and processes their results, and automatically recovers from any interruption. - Programmatic workflow management. Your workflows are stored as rows in a Postgres table, so you have full programmatic control over them. Write scripts to query workflow executions, batch pause or resume workflows, or even restart failed workflows from a specific step. This makes it much easier to diagnose and recover from bugs and failures that affect thousands of workflows. - Full support for both sync and async Python–write your workflows and steps as code either synchronously or asynchronously, it all works out of the box. - Improved tooling, including dashboards, workflow graph visualization, workflow management via web UI, and more. We’d love to hear your feedback and hope you can try DBOS out!
Does the same job
all alternatives →- LDLightweight Durable Workflows Built on Postgres2025 · github.com · ▲5
Hi HN! This is Qian here with Peter (KraftyOne) and Jeremy (jedberg). We’re building DBOS, an open-source, lightweight durable workflows library that you can add to Python apps in just a few lines of code. It’s comparable to popular open-source workflow and queue libraries like Airflow and Celery, but more lightweight with a greater focus on reliability and automatically recovering from failures. Our goal in building DBOS is to make workflows lightweight and flexible so you can add them to your existing apps with minimal work. Everything you need to run durable workflows and queues is…
- PBPostgres-Backed Durable Workflows in GoSep 2025 · github.com · ▲5
Hi HN - I’m Peter, here with Max (hmaxdml), and we’re building DBOS Go, an open-source Go library for durable workflows, backed by Postgres. https://github.com/dbos-inc/dbos-transact-golang DBOS workflows make your programs durable by automatically checkpointing their state to Postgres. If your program crashes or fails, all workflows seamlessly resume from their last completed step when your program restarts. This durability makes workflows useful for solving many different problems, including: - Operating an AI agent, or anything that connects to an unreliable or…
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