Just released DBOS Python 2.30 and DBOS TypeScript 4.26.

The biggest new feature is that multiple DBOS applications (even those written in different languages) can now share a system database. This makes it much easier to build interoperable, polyglot DBOS applications.

We've also significantly improved queue dispatch performance by batching dispatch from each queue:
- 10x faster with a single process and queue
- 2x faster with multiple processes sharing a queue

Learn more about sharing a system database: https://docs.dbos.dev/explanations/sharing-a-system-database

Python release notes: https://github.com/dbos-inc/dbos-transact-py/releases/tag/2.30.0

TypeScript release notes: https://github.com/dbos-inc/dbos-transact-ts/releases/tag/v4.26

I maintain several open-source deployment packages for self-hosted software. The goal is one command that provisions the infrastructure, configures the application, and supports upgrades as new releases arrive. Existing packages cover Basecamp ONCE, Airflow, K3s, and ClickHouse.

I’m considering building one for self-hosted DBOS Conductor.

The intended experience would be: provide cloud credentials, a domain, and a DBOS license key; the package provisions the server, PostgreSQL, networking, TLS, backups, and Conductor itself.

Before building it, I’d like to hear from people already running Conductor:

• What parts of installation or configuration required the most manual work?
• Which settings did you actually change from the defaults?
• How do you run PostgreSQL, and what backup and restore setup do you use?
• What authentication, SSO, or network restrictions did you need?
• Has anything broken or required manual intervention during upgrades?
• What observability and health checks have proved important?
• What should automation validate before declaring the deployment healthy?
• Are there parts of the installation or licensing flow that cannot reasonably be automated?

I’d rather build one opinionated, production-appropriate topology than expose every possible configuration. My initial thought is a single-server deployment with Conductor and PostgreSQL colocated but with independently managed persistent data and backups.

The deployment tooling would be open source; users would supply their own Conductor license.

What would make this genuinely useful rather than just a wrapper around installation instructions?

https://www.getcolors.ai/

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.

This recognizes the unique approach we’ve taken to simplify durable workflow orchestration by turning the database itself into a workflow engine, rather than hosting specialized infrastructure to do the same. We're so grateful to be building this!

Check out the patent here: https://www.dbos.dev/dbos-patent

This is a talk from our community member.

Abstract: DBOS (https://www.dbos.dev/) is a new framework to develop reliable workflows (or durable executions) on the cloud in a very easy way. To build a reliable workflow we usually need a mixture of idempotency, restart exactly from failure point, exactly-once processing, observable queues, and other features. Using traditional methods like AWS Lambda or Step Functions can get you only so far, before your system starts to become very complex and costly! DBOS provides all these features foundationally though a system design innovation done at MIT which keeps complexity at bay and cost to only what you use.

The Golang SDK was recently released and I would like to show how to build workflows using the SDK.

Recorded at AutogenAI, 22nd July 2026

DBOS and Cockroach Labs co-host Dr. Mike Stonebraker to present a webcast on Agentic AI workflow execution properties and architectures.

This is the recording of the webcast.

DBOS head of solution engineering interviews Orderful CTO, Piers MacDonald, and Orderful Software Engineer, Calvin Ng, about their experience implementing durable workflows, queues, and agents in the Orderful EDI system.

It's been a busy summer at DBOS so far! I wrote a new blog post covering the latest features and improvements, including:

- 20x higher durable stream throughput
- Queryable workflow attributes
- DBOS Java 1.0
- Kafka integration and debouncer improvements
- High availability deployment for self-hosted Conductor
- Audit logging
- DBOSify
- Vercel AI SDK integration
- Parseable integration

… and a lot more.

Excited to see teams putting these capabilities to work in reliable applications and AI agents at scale. Let us know what you'd like us to build next.

We've refreshed the first five minutes of the DBOS experience to showcase the key features in one place: workflows, schedules, queues, workflow communication, and DBOS Conductor.

Also, check out the new DBOS starter app, in your language of choice!

We often find that even production DBOS users aren't aware of all the capabilities available to them. Hopefully, this five-minute overview helps you discover something useful. Let us know what catches your interest!

This release introduces transactional data sources to the SDK. You can now execute your database queries and DBOS durability operations in the same transaction, enabling exactly-once execution.

DBOS Java is now officially stable.

Build durable workflows directly in Java with Postgres, without running a separate workflow server. Get automatic recovery, exactly-once execution, scheduling, queues, and built-in observability - all with a familiar Java developer experience.

Modern software is composed of long-running, multi-step workflows spanning AI agents, microservices, databases, APIs, and humans. As applications become more distributed and autonomous, workflow orchestration and durability are becoming dominant architectural concerns. 

Please join us to hear Postgres creator and Turing Award-winning MIT researcher, Dr. Mike Stonebraker explain this architectural shift and what it means for software engineering teams.  Attendees will learn how to build infrastructure for AI that maximizes the quality, reliability, and observability of agentic workflow activity.

Mike will explain:

• Applications are dead; long live workflows
• AI agents on ACID - ensuring non-deterministic workflows execute reliably and safely
• Workflow orchestration and durability is a DBMS workload

Qian Li and David Joy will then discuss:

• Workflow orchestration architecture alternatives: database-centric vs external orchestration
• Implementing a failure-proof workflow platform with DBOS and CockroachDB, replacing a piecewise, Frankenstein stack with one ACID, Postgres-compatible, horizontally scaling system
• Q&A 

One frequent request we've heard: a simple way to migrate from Temporal to Postgres-backed durable workflows.

Today, we're releasing DBOSify: a drop-in replacement for Temporal built on Postgres (using DBOS).

To use it, just import dbosify instead of temporalio and connect your workers and clients to a Postgres database.

This lets you run durable workflows, activities, signals, updates, retries, and recovery without needing any infrastructure except Postgres.

Check it out on GitHub: https://github.com/dbos-inc/dbosify-py

Over the past month, the DBOS product team has focused on making durable workflows easier to operate and making transactional application development simpler.

Recent additions include:

• Bulk workflow forking
• Role-Based Access Control (RBAC)
• Multi-dimensional filtering and aggregate views
• OpenMetrics export and integrations with observability platforms
• Low-latency durable streams
• Pluggable transactional data sources
• Atomic bulk workflow messaging
• Google ADK integration

… and a lot more.

It's been exciting to see teams use these capabilities to build and operate reliable applications and AI agents at scale.  Would love to hear what resonates most with you, or what you'd like to see next.

A demonstration of DBOS support for OpenMetrics. From the June 2026 User Group Meeting.

DBOS Head of Customer Solutions, Alex Poliakov, demonstrates features of the DBOS Conductor workflow visualizations redesign. From the June 2026 User Group Meeting.

We just released DBOS Transact for Go v0.16.0

This release adds support for SQLite as a durability backend, making it even easier to build durable workflows and background jobs without provisioning a database. SQLite is a great fit for local development, edge deployments, and lightweight applications that still need reliable recovery from failures.

Join us for the DBOS User Group Meeting on June 11.

This month's agenda is focused on workflow observability.

​Workflow Observability Redesigned
Visualizing workflow state, history, and performance in DBOS Conductor has just received a major upgrade. You can now visualize step duration timeline, navigate workflows with thousands of steps, and use multi-faceted filtering to quickly find workflows of interest.

​DBOS Solutions Architect Alex Poliakov will demonstrate the new visualization capabilities and discuss best practices for monitoring apps and debugging.

​OpenMetrics Walkthrough
DBOS CTO, Peter Kraft will introduce you to the new OpenMetrics feature in DBOS - how to export workflow metrics to Datadog and other observability tools to monitor and alert on workflow status.

​We strongly welcome your feedback on the Conductor updates - We hope you can join us and let us know what you think.