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OrioleDB is now in public beta, on every Supabase plan. It changes how Postgres stores your table rows, so in most cases they don’t bloat as your data changes. Learn more →

30,633 views • 5 days ago •via X (Twitter)

10 Comments

Kuldeep Pisda's profile picture
Kuldeep Pisda5 days ago

so the bloat moves into the undo log instead, curious how big that gets with a long analytics query holding a snapshot

Sachin's profile picture
Sachin5 days ago

postgres table bloat has been the silent tax on every busy app autovacuum about to get a lot less screen time

Agentik's profile picture
Agentik5 days ago

does it play nice with pgvector?

E1ev3n.'s profile picture
E1ev3n.5 days ago

Table bloat is the silent killer I know too well. I have watched my own side project slow down for no obvious reason, only to find the database had quietly ballooned. A storage engine that stops the bloat before it starts is the kind of fix I would take in beta, risks and all.

Hershal Rao's profile picture
Hershal Rao5 days ago

finally my write-heavy queue tables can stop gaslighting me

Sujal's profile picture
Sujal5 days ago

Does it work on existing tables or only on ones you create after turning it on?

Kalu's profile picture
Kalu5 days ago

public alpha in dec 2024, public beta now, still not for prod. see you at ga in 2028?

Anand Butani's profile picture
Anand Butani5 days ago

Postgres bloat is a quiet tax that pushes startups into pricier database plans and cleanup jobs. If OrioleDB holds up, the real win is smaller bills

Mohammad Vazin's profile picture
Mohammad Vazin5 days ago

OrioleDB's undo-log design means updates stop leaving dead tuples for autovacuum to chase. The real test for me is write-heavy queue and session tables, which is where we've always fought bloat and vacuum tuning hardest.

RusticStack's profile picture
RusticStack5 days ago

OrioleDB doesn't do Postgres's predicate-lock SSI, so SERIALIZABLE behaves differently there. The default orioledb.serializable = table_lock takes an ExclusiveLock on every table the transaction touches, and serializable writers on the same table end up running one at a time.

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