Or don't. You know that combination is tempting fate.
I love postgres. It's so great. The very best thing I can say about software is you have to tempt fate to get bitten by a bug.
don't do that if you value your uptime at all. Long-running transactions are the bane of any Postgres setup, no matter the XID overflow.
A few weeks ago, one slipped through my monitoring and a cache table we often sequence scan which normally had 10k rows in it had 28M dead rows that could never be removed due to that one transaction.
That sequence scan suddenly became a lot more expensive.
It depends on the write load, the read load, and the write patterns.
Think about it this way: for the duration of any transaction, Postgres is basically in append-only mode.
If you have cache tables that normally get rewritten entirely, no row will be deleted during the duration of any transaction in the whole cluster (so this even affects databases other than the one the transaction is connected to).
In our case, we run some heavy import jobs daily which causes transaction lifetimes in hours, depending on the job. This isn't an issue, or rather, it's an issue, you can throw hardware at in order to circumvent it.
The transaction I was referring to in my earlier comment had a lifetime in days and nearly brought down the whole system.
See http://thebuild.com/presentations/uber-perconalive-2017.pdf
Still. I have had MySQL corrupt tables with way less load and data (in the less than 10GB size range)
The company here is doing petabytes of data and millions of ops per second. That’s scale.
We should be clear about what “at scale” means, and 6.2TB is not.
If table corruption is acceptable, you might as well just serve data from /dev/urandom and store user data to /dev/null.
How many Uber rides are happening every second? I suppose it depends exactly on their setup, but I could see that being at least the right order of magnitude.
EDIT: According to the Internet, there are about a billion Uber rides per year, which makes for about 31 rides per second. Even if there are 1000 transactions per ride, 21k/second sounds approximately Uber scale to me.
I'm not convinced. The one feature I really need a database to have is to guarantee that whatever data I write to it, I will be able to read back unaltered.
I'm a heavy Postgres user since 2001 and I have never seen table corruption, even in the face of defective hardware. The only time something remotely comparable has happened was index corruption on a replica due to a bug in 9.2.0 which was very quickly fixed and as it was just a corrupted index, very easily restored (REINDEX).
If a database I trust with production data was corrupting tables, I would move off that system in a heartbeat (which is incidentally why I stopped using MySQL back then)