February 16, 2026
Dev war: Is it Postgres or your code?
Testing Postgres race conditions with synchronization barriers
Postgres race-test sparks dev brawl: “Fix your code, not the DB”
TLDR: A simple testing “barrier” reliably exposes money-eating race bugs by forcing bad timing on purpose. Commenters split: some say write proper SQL or use stored procedures, others push advisory locks or strict SERIALIZABLE mode, and testing nerds tout tools like Loom to explore every timing edge case.
Money vanished in testing and the internet grabbed popcorn. A new post shows how a “synchronization barrier” forces two actions to pause at the same point, so they both read the same old balance before anyone writes. Boom—your race condition appears on command, like two $50 deposits mysteriously turning into $150 instead of $200. The tool is simple; the drama is not.
The loudest chorus? “This isn’t Postgres, it’s your code.” One commenter wagged a finger: just do a single atomic UPDATE or use stored procedures—“why are you doing transactions in JavaScript?” Another took it further with a dunk on JS devs needing “kindergarten basics.” Meanwhile, the pragmatists brought receipts: use advisory locks (a DB feature to coordinate tricky logic when there’s no row to lock), or crank the SERIALIZABLE isolation level (Postgres’s strictest mode) and let the database reject unsafe transactions.
Then the testing purists showed up with lab coats: barriers are great, but what about every possible timing? Cue Loom, a Rust tool that explores different orderings of events. The vibe: barriers prove a bug you suspect; Loom-style tools try to find the ones you don’t. In short, it’s a dev civil war with memes (“The database did exactly what it was told”) and a moral: testing concurrency is hard—so pick your weapons wisely.
Key Points
- •The article demonstrates a classic lost update race condition in a read-modify-write sequence for account credits.
- •Standard test suites often miss concurrency bugs because they run sequentially and rely on chance for interleavings.
- •A synchronization barrier waits for N tasks and releases them simultaneously, enabling deterministic interleavings.
- •Placing the barrier between read and write forces all tasks to read stale values before any writes, reproducing the race.
- •Applying the barrier to a naive credit function shows how to reliably surface and test concurrency issues with bare queries.