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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Database-Backed Durable Python Workflows
| Date | Stars |
|---|---|
| 2026-07-24 | 1488 |
| 2026-07-25 | 1494 |
| 2026-07-28 | 1494 |
| 2026-07-30 | 1494 |
| 2026-08-06 | 1494 |
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35.0
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<div align="center">
[](https://github.com/dbos-inc/dbos-transact-py/actions/workflows/unit-test.yml)
[](https://pypi.python.org/pypi/dbos)
[](https://pypi.python.org/pypi/dbos)
[](LICENSE)
[](https://discord.com/invite/jsmC6pXGgX)
# DBOS Transact: Lightweight Durable Workflows
#### [Documentation](https://docs.dbos.dev/) • [Examples](https://docs.dbos.dev/examples) • [Github](https://github.com/dbos-inc) • [Discord](https://discord.com/invite/jsmC6pXGgX)
</div>
---
## What is DBOS?
DBOS provides lightweight durable workflows built on top of Postgres.
Instead of managing your own workflow orchestrator or task queue system, you can use DBOS to add durable workflows and queues to your program in just a few lines of code.
To get started, follow the [quickstart](https://docs.dbos.dev/quickstart) to install this open-source library and connect it to a Postgres database.
Then, annotate workflows and steps in your program to make it durable!
That's all you need to do—DBOS is entirely contained in this open-source library, there's no additional infrastructure for you to configure or manage.
## When Should I Use DBOS?
You should consider using DBOS if your application needs to **reliably handle failures**.
For example, you might be building a payments service that must reliably process transactions even if servers crash mid-operation, or a long-running data pipeline that needs to resume seamlessly from checkpoints rather than restart from the beginning when interrupted.
Handling failures is costly and complicated, requiring complex state management and recovery logic as well as heavyweight tools like external orchestration services.
DBOS makes it simpler: annotate your code to checkpoint it in Postgres and automatically recover from any failure.
DBOS also provides powerful Postgres-backed primitives that makes it easier to write and operate reliable code, including durable queues, notifications, scheduling, event processing, and programmatic workflow management.
## Features
<details open><summary><strong>💾 Durable Workflows</strong></summary>
####
DBOS workflows make your program **durable** by checkpointing its state in Postgres.
If your program ever fails, when it restarts all your workflows will automatically resume from the last completed step.
You add durable workflows to your existing Python program by annotating ordinary functions as workflows and steps:
```python
from dbos import DBOS
@DBOS.step()
def step_one():
...
@DBOS.step()
def step_two():
...
@DBOS.workflow()
def workflow()
step_one()
step_two()
```
Workflows are particularly useful for
- Orchestrating business processes so they seamlessly recover from any failure.
- Building observable and fault-tolerant data pipelines.
- Operating an AI agent, or any application that relies on unreliable or non-deterministic APIs.
[Read more ↗️](https://docs.dbos.dev/python/tutorials/workflow-tutorial)
</details>
<details><summary><strong>📒 Durable Queues</strong></summary>
####
DBOS queues help you **durably** run tasks in the background.
You can enqueue a task (which can be a single step or an entire workflow) from a durable workflow and one of your processes will pick it up for execution.
DBOS manages the execution of your tasks: it guarantees that tasks complete, and that their callers get their results without needing to resubmit them, even if your application is interrupted.
Queues also provide flow control, Excerpt of 12,996 characters
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Qian Li · @dbos-inc
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Ben Drucker · United States
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e63d03b3d58741db, topic:agentic-workflow, readme:ai agent
matched fp:e63d03b3d58741db, topic:orchestration