GoKawiilPostgres engineers detail how to make DELETE perform at scale
A technical blog post explains optimizations for using Postgres DELETE efficiently rather than resorting to table truncation or partition dropping. The authors applied tuning techniques—focused on cache and index performance—to a Postgres-backed durable workflows and queues system handling tens of thousands of workflows and steps per second, in order to enforce data retention policies.
GoKawiil's interpretation of the reporting above, not reported fact.
The post pushes back on a common engineering assumption that DELETE is inherently unscalable in Postgres, which could encourage teams building high-throughput systems to retain DELETE's flexibility instead of defaulting to coarser deletion strategies like dropping partitions. Because Postgres relies on MVCC, deletes carry extra overhead compared to bulk operations, so the techniques described may be particularly relevant for systems with heterogeneous data retention needs.
- Postgres DELETE is often avoided in high-performance systems due to MVCC-related overhead.
- The authors applied cache and index optimizations to make DELETE viable at scale in a workflow/queue system.
- The approach was tested on a system processing tens of thousands of workflows and steps per second.
Source: dbos.dev, 2026-10-15
Published there as: “How Postgres DELETE can actually scale”
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