TL;DR
A recent discussion advocates replacing external workflow orchestrators with direct Postgres integration for durability. This approach simplifies architecture, enhances scalability, and leverages Postgres’s robust features for observability and security.
Developers are now increasingly using Postgres as the primary system for managing durable workflows, replacing traditional external orchestrators. This shift aims to simplify architecture, improve scalability, and leverage Postgres’s native features for observability and security.
Traditionally, durable workflows rely on external orchestrators like Temporal or Airflow to manage checkpointing and task dispatching. These systems coordinate workflow steps through a central server, which can introduce complexity, single points of failure, and scalability challenges. Recent discussions suggest that using Postgres directly as the orchestrator — with application servers polling and checkpointing directly to database tables — can eliminate the need for separate orchestration layers. This approach allows application servers to coordinate via database locking mechanisms, with Postgres handling concurrency, consistency, and failure recovery. Because Postgres is a mature, scalable, and reliable database system, it can support high throughput and availability, especially with features like streaming replication and sharding. Additionally, storing workflow state in relational tables enables powerful, SQL-based observability, making it easier to monitor and analyze workflow execution in real time. This method reduces operational complexity and leverages existing Postgres expertise, potentially lowering costs and increasing robustness.
Why It Matters
This approach matters because it simplifies the architecture of durable workflow systems, making them easier to operate, scale, and secure. By removing external orchestrators, organizations can reduce points of failure, improve observability, and rely on well-understood database technology. This could lead to more reliable systems, especially at scale, and lower operational overhead. Moreover, it aligns with the trend of using familiar, proven infrastructure to build complex, reliable applications.
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Background
Durable workflows have traditionally depended on external orchestrators like Temporal, Airflow, or AWS Step Functions, which manage workflow state and task dispatching. These systems, while powerful, introduce additional complexity, operational overhead, and potential failure points. Durable sell off will tie to Fed interest rate hikes. Recent discussions in developer communities, including insights shared on Hacker News, highlight the possibility of using Postgres as the core component for durable workflows. This idea builds on decades of research and engineering into Postgres’s scalability, reliability, and rich feature set, making it an attractive alternative for organizations seeking simplicity and robustness.
“Replacing a central orchestrator with Postgres makes durable workflows fundamentally simpler, leveraging Postgres’s native solutions for scalability, observability, and security.”
— Hacker News contributor
“Postgres’s relational model and query optimization enable powerful, SQL-based observability, making real-time monitoring of workflows straightforward.”
— Postgres expert
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What Remains Unclear
It is not yet clear how well this approach scales in very high-throughput environments or how it handles complex dependency management in workflows. Additionally, practical implementations and performance benchmarks are still emerging, and some organizations may face challenges adapting existing workflows to this model.
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What’s Next
Next steps include developing more comprehensive implementations and benchmarks to evaluate performance and reliability. Organizations interested in this approach will likely experiment with integrating Postgres as their workflow backbone, while vendors and open-source projects may start offering tools and frameworks to facilitate this pattern. Further research and case studies are expected to validate its effectiveness at scale.
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Key Questions
Can Postgres handle very high workflow throughput?
While Postgres can scale vertically and horizontally with sharding or distributed variants, its performance in extremely high-throughput scenarios depends on specific workloads and configurations. More benchmarks are needed to confirm its limits.
How does this approach compare to traditional external orchestrators?
Using Postgres directly reduces architectural complexity, operational overhead, and points of failure. However, it may require more careful design to handle complex workflows and dependencies.
What are the security implications of using Postgres as the workflow store?
Because Postgres handles sensitive workflow data, it must be properly secured with access controls, encryption, and auditing, similar to other critical infrastructure.
Is this approach suitable for all types of workflows?
It is most suitable for workflows that can be effectively checkpointed and managed via database transactions. Complex workflows with intricate dependencies may require additional planning.
Source: Hacker News
