Importance of Tuning Checkpoint in PostgreSQL

One tweak tames Postgres slowdowns — Oracle fans stir

TLDR: Tuning one Postgres setting can smooth out performance and slash log churn, turning spiky slowdowns into steady speed. A lone Oracle shoutout revived the old debate: pay big for turnkey reliability or tweak open‑source for free, reminding everyone that cost vs. time is the eternal trade‑off.

PostgreSQL pros are begging newbies: tune your “checkpoint” settings or watch your server yo-yo. A checkpoint is a safety save—Postgres makes sure data is consistent—then, right after, it logs whole pages (called Full-Page Images) the first time they’re touched, which can slam your disks. The blog’s test shows the fix is simple: spread checkpoints out and the database chills—log files dropped from 12GB to 2GB, and those heavy full-page writes fell 9x. Translation: fewer spikes, smoother rides, happier ops.

But the real fireworks? One top comment from user chasil swooned over Oracle’s “rock solid” logs and standby replicas, then dropped the price bomb ($17,500–$47,500 per core) and a cheeky “I should learn a better alternative than SQLite.” Cue the oldest internet flame war: pay for Oracle’s peace-of-mind vs. roll up your sleeves and tune Postgres. It’s the classic three-way split—tinkerers (“free, but read the manual”), check-writers (“expensive, but sleeps like a baby”), and the minimalist crowd who jokes that SQLite is a spreadsheet with dreams.

Memes practically write themselves: “Oracle tax vs. open-source sweat equity,” “sawtooth graphs need a dentist,” and “checkpoint chiropractor, adjust my I/O.” Under the drama, one point stands tall: Postgres can be buttery smooth—if you tweak it. The rest is a vibe war over paying in dollars or paying in time. Learn more in the PostgreSQL docs.

Key Points

  • PostgreSQL checkpoints ensure storage-level consistency and serve as the starting point for recovery using WAL.
  • Checkpoint processing includes identifying dirty buffers, spreading writes via checkpoint_completion_target, fsyncing files, updating global/pg_control, and recycling WAL segments.
  • Post-checkpoint performance dips are largely due to Full-Page Image (FPI) writes required on first page modification after a checkpoint.
  • Benchmarking with pgbench (1,110,000 transactions) across different checkpoint durations shows WAL generation can drop from 12 GB to 2 GB.
  • FPI writes can be reduced from 1.47 million to 161 thousand by extending checkpoint intervals, significantly lowering I/O.

Hottest takes

“Expensive as it is… the archived logs are mostly rock solid” — chasil
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