DBOS
@dbos
Build reliable backends effortlessly. Website: dbos.dev Open source:
Six years ago, DBOS started as a joint research project at MIT and Stanford on applying database principles to modern applications. Today we announced a major milestone: the issuance of U.S. Patent for our database-centric durable workflow architecture.
What if your AI agents were built on ACID transactions? Join Postgres creator Mike Stonebraker to learn why transactional databases are becoming the foundation for reliable AI agents and agentic workflows. This is a joint webinar with @cockroachdb.bsky.social Thursday, July 16, 2 PM ET/11 AM PT.
We just released the much-requested Google ADK + DBOS integration: durable execution for ADK agents, backed directly by your database. - Official Google ADK doc: adk.dev/integrations... - DBOS ADK plugin repo: github.com/dbos-inc/dbo... - DBOS doc: docs.dbos.dev/integrations... Feedback welcome!
Published a new blog post covering the latest batch of features and integrations we shipped this past month. We focused on two areas that matter a lot in production: interoperability and privacy-preserving operations. Read the full update here: dbos.dev/blog/dbos-ne...
Cool new feature: Dynamic workflow schedules! The idea is to store workflow schedules in Postgres so you can dynamically create, view, update, and delete them at runtime, as well as (coming soon) view them from a dashboard. Plus, our new design supports backfilling and manual triggering.
Fivetran - DBOS webinar tomorrow, Jan 28 at 9AM PT/12PM ET Learn how to build a control plane that safely manages Fivetran Connector SDK state changes using DBOS durable workflows. It enables idempotency, automatic recovery, and enterprise-grade reliability‚ without complex custom orchestration.
A nice feature in the latest DBOS Python release: you can now call async steps concurrently with native syntax from a workflow. To make that possible, we added code to set a unique ID for each step before it begins, so even though the step executions overlap they’re checkpointed deterministically.
2025 has been a wild year for DBOS. Huge thanks to you all for the support, feedback, and trust along the way. Looking forward to making reliable software even easier to build in 2026 🚀
Cool new feature: explicit queue listening! You can now configure exactly which queues each of your workers listens to. This is especially helpful if you have heterogeneous workers (such as some workers for GPU tasks and others for CPU-intensive tasks) as you can easily divide work between them.
What happens when applications are written almost entirely by LLMs? @andypavlo.bsky.social explains what’s already happening, and why future enterprise apps may start with vibe coding.
Goblins moved from external workflow services to DBOS for faster execution, a unified stack, and full control over debugging and uptime. Alp said "when your database is essentially one millisecond away from your servers, every workflow is just blazing fast.”
For Ontologize, reliably spinning up enterprise software environments at scale required durability and simplicity. DBOS let them scale their deployment pipeline with Python and zero rearchitecting.
Durable execution is underrated. In real systems, any step can fail at any time. Peter breaks down why reliability is such a challenge.
Thanks QCon for having @qianli.dev and @jedberg.net. Their talk covered how durable computing and DBOS Transact boost reliability, remove heavyweight workflow coordinators, and reduce both complexity and cost.
Building reliable AI systems is hard. In this video, @petereliaskraft.net walks through a deep research agent that many of us want to build and the kind that fails in all the surprising ways. Failures are inevitable and a durable workflow is what will make your agent production ready.
When Yutori looked into Temporal, the cost was clear. It would mean rearchitecting their workflows. With DBOS, they could orchestrate durable workflows using just a few Python decorators and a Postgres database.
Celery’s familiar. But once tuning and load management start piling up, things get messy fast. DBOS changes that.
If you’ve ever wondered why your queue is filling up, this one’s for you. Cameron shares how DBOS’s Grafana dashboard helps them see every job, every queue, and fix stuck workflows before things go sideways.
When reliability is built in, devs can focus on solving real problems instead of managing infra. Hear what Cameron Spiller from Soria Analytics has to say about it.
Just launched the official @supabase.com integration with DBOS! Power your workflows with Supabase Postgres: - Add workflows in just a few lines of code - No new dependencies: just your app and Supabase - See your workflow data from the Supabase dashboard Here's a quick start guide 👇
The team at Goblins has been cooking with DBOS. Catch Co-founder & CTO Alp as he showcases their app at the next DBOS User Group.
Most systems treat durability as optional. But failures aren’t rare, they’re inevitable. Servers crash, containers restart, network calls fail, and logic errors surface in production. Each time this happens, devs scramble to rebuild context, retry operations, or recover partially completed work. 🧵
What’s the real impact of switching to DBOS? Simpler workflows, better observability, lower infra costs. Hear how it transformed productivity for Dosu.
As LLMs and agents become the foundation of modern software, every stack needs durability and state recovery. DBOS brings that to any agent stack, without the complexity. Hear what Devin from Dosu has to say.
Versioning in DBOS Cloud makes deployments clear and reliable, here’s how Yutori is using it: ✅ Every new release spins up its own VM ✅ Logs are tagged by version, so you know which release produced them ✅ Full observability across versions without losing context
Guess who’s coming to September’s Reliable RAG and Agentic AI user group? The creator of Postgres. Mike Stonebraker himself. 📍Join Us: luma.com/c3hsxk3f 🗓️ Thu, Sep 25 | 11 AM PDT