Alternatives
Products that do what Lightweight Durable Workflows Built on Postgres does
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…
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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,…
2025 · github.com
- 2PB
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…
Sep 2025 · github.com
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Atlas is an open-source deployment pipeline platform built for cloud-native applications. Atlas allows users to: - Create continuous pipelines across all their environments and clusters - Add custom tasks/tests plugins (Python scripts, K8S manifests, Argo Workflows, environment setup, etc.) - Automatically rollback applications in case of failure or degradation (Atlas watches the application past the scope of a pipeline run to ensure and enforce stability) - Use all existing Argo features Would love to hear all of your feedback and thoughts on this!
2022 · greenops.io
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- 6RW
Hey HN, I'm Anurag, founder and CEO of Render, a cloud for application developers. We've just launched Render Workflows, a way to define durable tasks by decorating plain TypeScript or Python functions and running them on Render without operating queues, worker pools, retry logic, and state management. Code example below [1]. The use cases we have in mind include agent loops, ETL/data pipelines, billing flows, and other long-running jobs. The model is simple: mark an existing function as a Task, deploy the repo as a Workflow, then trigger runs from your application code or via our API.…
Apr 2026 · render.com
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2014 · databaselabs.io
- 8AD
I'd like to share a project I've been working on for the past few months. It's a distributed workflow engine written entirely in Go. Some highlights: * Tasks are executed in a Docker container * Can run stand-alone or distributed * Highly extensible * Able to enforce limits (CPU/RAM) per task * Web UI Would love the get your feedback on it, and find out if this could be useful.
2023 · github.com
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Hey everyone, we just released a new version of our Infrastructure as Code Python SDK that now runs entirely on your machine - no account required. LaunchFlow extends OpenTofu to provide features like multi-environment support [1], autoconfigured infrastructure clients [2], and API release management [3]. Our goal is to provide a Python-native infrastructure toolkit that handles everything from automating your infrastructure to using it in your application code. You can use our library of preconfigured OpenTofu modules to add GCP / AWS infrastructure to your app with just a few lines of…
2024 · launchflow.com
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2021 · flowdash.com
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At work we were using python-rq for background tasks. It does the job for simple things, but we kept bumping into limitations. We needed to schedule tasks hours / days out and trust they'd survive a restart. We wanted periodic tasks with proper overlap control. So we built a scheduling / enqueuing system around Postgres to bring these durability capabilities to python-rq. This worked fine for a while but was trickier to reason about due to its more complicated architecture (we'd run two separate services just for getting jobs from Postgres into the rq Redis queue, plus N actual…
Feb 2026 · github.com
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I'm a couple years late to the party but DuckDB is blowing my mind. I couldn't find an good embedded DuckDB stream processing solution so I hacked my own, calling it SQLFlow: https://github.com/turbolytics/sql-flow SQLFlow enables writing stream transformations in pure sql, executed using DuckDB. The goal was to create a lightweight, performant stream processing engine using pure SQL transformations, DuckDB didn't disappoint! I'd love your feedback, feature requests, impressions, or just comments. I'd love to turn this into a stable, usable project that people are…
2023 · github.com
- 14PP
I’ve found that I don’t have any context about the data in my pipelines only know if the pipeline is successful or not. So I built panda-patrol which allows you to monitor each node in your DAG, use AI to generate data tests for your data, store data profiles, and more. All with this comes with dashboards and alerts. You can easily drop it into your Python-based data pipeline (i.e. Airflow, Dagster, Prefect, etc.) and just run your pipelines are you normally would — but with monitoring and more context. Hope its valuable to some people
2023 · panda-patrol.vercel.app
- 15PP
Hi, the main motivation of this small personal project is the ability to build Postgres-backed python apps that remain fully pip-installable despite the dependency, while saving your users any need to setup Postgres if they don't have it. It also helps me, as a developer, to not have to remember how to set up postgres, which I find is one main barrier to using it for small stuff. It's a little project of mine that may be helpful to more people. I'm curious to hear your feedback (ps. I know about SQLite, but sometimes you want/need to build against postgres)
2024 · github.com
- 16IM
Hello HN, I've just released a new migration tool for Go that mimics the functionality of Ruby on Rails migrations. It's designed to help Go developers manage database schema changes with ease. This allows you several benefits: - Write type-safe migrations - Auto down of migrations whenever it's possible - Easy backfill even with business logic because it's Go code - Painless integration with existing schema - sql.DB compatible and driver agnostic (it uses your driver) I have a pretty complete API to manage Postgres schema and I am working on the SQLite one (a little more complicated due to…
2024 · github.com
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My name is Elliott. For the last three years, I’ve been building a DevOps platform on the best-in-class open source platforms (Kubernetes, Elixir, PostgreSQL, Grafana, etc.). The goal is to give engineering teams access to a modern DevOps infrastructure without needing to have a full SRE/DevOps team dedicated. It’s also open source /fair source - all the source code is here → https://github.com/batteries-included/batteries-included I shipped a public beta today and would love to hear initial reactions, thoughts, and feedback. Here are details of the platform: *…
2024 · batteriesincl.com
- 18DR
We’ve built SQLRooms, an open-source framework for creating single-node data analytics apps powered by DuckDB. It lets you build fully client-side, data-centric apps using React and DuckDB running in the browser (via WebAssembly) or in Electron. No server or backend is required — apps can work offline, preserve data privacy, and run queries on large datasets with sub-second performance. Features: - Query large datasets in browser with DuckDB (WASM) - Modular design for building composable data UIs (query editors, dashboards, notebooks, etc.) - Data privacy-preserving AI assistant that can…
2025 · sqlrooms.org
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Hi HN, Over the past year, I’ve been building a native MacOS Postgres client for my personal use. While there are plenty of existing clients, I built this because: - No open-source Postgres client matched the smooth UX of tools like Sequel Pro/SequelAce (for MySQL). - I missed the satisfaction of long-term product ownership and iteration—recent work has me jumping between projects. - I’ve been using Postgres more lately and wanted to get hands-on to deepen my knowledge. I also wanted a playground to experiment with client features that would help me on day-to-day. Some I have…
2025 · github.com
- 20AJ
I have created a Cron alternative that runs DAGs (Directed acyclic graph) defined in a simple YAML format. Why not Airflow? Airflow and other similar tools are powerful and valuable, but in most cases, they require writing code to manage workflows. Our ETL pipeline is already hundreds of thousands of lines of complex code in Perl and shell scripts. Adding another layer of Python on top of this would make it difficult to maintain. Instead, we needed a more lightweight solution. So we developed Dagu, which requires no coding, and is easy-to-use and self-contained, making it ideal for smaller…
2022 · github.com
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Hi HN, we’re Jessie and Eric. We’ve been baking away at Cakework (https://www.cakework.com/), which is a way to build async backends without needing to manage cloud infrastructure. Cakework is for operations that take time or more compute, like file processing, report generation, or machine learning. Devs write backends as Python functions and deploy them with our CLI. They use our client SDKs to make requests, get status, and get processing results. Each request runs with its own CPU and memory parameters in its own microVM, with no timeouts. Devs can query for failures and…
2023 · cakework.com
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Hey HN, We’re excited to share PySpur, an open-source tool that provides a graph-based interface for building, debugging, and evaluating LLM workflows. Why we built this: Before this, we built several LLM-powered applications that collectively served thousands of users. The biggest challenge we faced was ensuring reliability: making sure the workflows were robust enough to handle edge cases and deliver consistent results. In practice, achieving this reliability meant repeatedly: 1. Breaking down complex goals into simpler steps: Composing prompts, tool calls, parsing steps, and branching…
2024 · github.com
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Hey HN, half a year ago we were building a feature where our users could trigger long-running jobs with the following requirements: (i) the job is provisioned by the user action (e.g., clicking a button in the UI), (ii) the job can be canceled by the user, (iii) the progress of the job can be inspected while the job is running, (iv) hardware for the job is provisioned only when needed (the job may require expensive hardware and isn't called that frequently). Because we couldn't find any existing ways of achieving this we decided to implement one for Python. Currently, it uses an AWS ECS…
2023 · github.com
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