Replace Your Workflow Engine with Just Postgres

Developers are using standard Postgres features to build and manage complex workflows, eliminating the need for separate, specialized orchestration tools.

A detailed architectural pattern, outlined in a recent InfoQ article by Raman Varma, demonstrates how engineering teams can build robust workflow systems using a tool they already have: the Postgres database. This approach sidesteps the need for dedicated external orchestrators, which are specialized services designed to manage complex, multi-step processes. By treating Postgres as both the durable state store and the coordination layer, developers can manage everything from simple background jobs to long-running business processes involving human approvals. The core idea is to leverage the database's inherent reliability and transactional guarantees to create a resilient system without adding another complex component to the technology stack. This method allows workflows to persist their state directly in database tables, ensuring that processes can survive application restarts, server crashes, and other common failure scenarios, making the entire system more durable and easier to manage.

The magic behind this technique lies in combining several powerful, yet standard, Postgres features. The primary mechanism for enabling concurrent work is the `SKIP LOCKED` clause, which allows multiple worker processes to query a task queue table simultaneously. When a worker selects a job, it locks that specific row, and `SKIP LOCKED` tells other workers to simply ignore the locked row and move on to the next available one. This prevents race conditions and ensures that no two workers attempt to process the same task. To guarantee that tasks are executed exactly once, a concept known as idempotency, the pattern uses primary-key constraints as checkpoints. Each step in a workflow is recorded with a unique key, so if a process fails and retries, the database will reject the duplicate entry, preventing the step from running again. Finally, the system uses leases—database records with an expiration timestamp—to handle crash recovery. If a worker fails mid-task, its lease expires, allowing another worker to safely take over and complete the job.

This pattern emerges within a broader industry trend toward architectural simplification and leveraging existing, trusted technologies for new purposes. For years, the default solution for complex workflows has been to adopt specialized tools like Temporal, Cadence, or cloud-native services like AWS Step Functions. While incredibly powerful, these systems introduce significant operational overhead, requiring teams to learn, deploy, and maintain a separate, complex piece of infrastructure. The Postgres-based approach offers a compelling alternative for teams that value simplicity and want to minimize their dependency footprint. It reflects a growing understanding that general-purpose databases, particularly mature ones like Postgres, are often more capable than they are given credit for. By pushing more logic into a well-understood and battle-tested data layer, teams can reduce the number of moving parts in their architecture, which often leads to more stable and predictable systems.

For CTOs and engineering leaders, this architectural choice presents a practical trade-off between simplicity and feature-richness. Adopting a Postgres-native workflow system can dramatically lower costs and reduce the cognitive load on developers, as they can work within a familiar environment. It is an especially attractive option for organizations that are already heavily invested in the Postgres ecosystem. However, this approach means forgoing the sophisticated user interfaces, observability dashboards, and advanced debugging tools that come standard with dedicated orchestration platforms. The decision ultimately depends on the specific needs of the application. For many use cases, the simplicity and cost-effectiveness of the database-centric model will be the winning combination. Looking ahead, we can expect to see more open-source libraries and frameworks emerge to formalize this pattern, making it even easier for teams to build durable, reliable workflows directly on their database.

This pattern allows engineering teams to consolidate their stack by leveraging a familiar tool, Postgres, for a new purpose. It reduces the complexity and operational burden of managing a separate workflow orchestration system, leading to a more streamlined, resilient, and maintainable architecture.

Companies can significantly reduce infrastructure costs by eliminating dedicated workflow orchestration software and its associated licensing or hosting fees. This approach also simplifies the tech stack, potentially accelerating development cycles and lowering the total cost of ownership for complex applications.