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Keeping a Postgres queue healthy
By Simeon Griggs | April 10, 2026
A healthy digestive system is one that efficiently eliminates waste. Fiber is a key part of a healthy diet, not because it is nutritious, but because it keeps everything you consume moving.
Databases are not so different. If you want a healthy queue table, you'll need to monitor the systems that are designed to perform cleanup well before they're backed up.
Postgres has been a popular choice for queue-based workloads long before it was a good fit for the job. Over many years and multiple major versions, Postgres has only become an even stronger choice for this type of workload.
But what makes job queues uniquely problematic? And in spite of all these advancements, what traps remain?
It's worth knowing, since they could bring down not only your job queue but also your mixed-workloads database and your entire application.
The "just use Postgres" meme lends credence to the notion that every workload belongs in a Postgres database. It's not the worst idea. You really can throw just about anything at a Postgres database and make it stick. The rich extensions ecosystem fills any functionality gaps in "vanilla" Postgres.
As a result, you may have multiple distinct workload types running in the same database at the same time. Your OLTP, OLAP, Time Series, Event Sourcing, Full Text, Geospatial, and/or Queue workloads may all be running at the same time in the same database cluster with different needs, challenges, and priorities—while competing for the same resources.
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