alt Hacker NewsI don't feel like it's easy to self-host postgres.
Here are my gripes:
1. Backups are super-important. Losing production data just is not an option. Postgres offers pgdump which is not appropriate tool, so you should set up WAL archiving or something like that. This is complicated to do right.
2. Horizontal scalability with read replicas is hard to implement.
3. Tuning various postgres parameters is not a trivial task.
4. Upgrading major version is complicated.
5. You probably need to use something like pgbouncer.
6. Database usually is the most important piece of infrastructure. So it's especially painful when it fails.
I guess it's not that hard when you did it once and have all scripts and memory to look back. But otherwise it's hard. Clicking few buttons in hoster panel is much easier.
Replies
Scaling to a different instance size is also easy on AWS.
That said a self hosted DB on a dedicated Hetzner flies. It does things at the price that may save you time reworking your app to be more efficient on AWS for cost.
So swings and roundabouts.
"all scripts and memory to look back. But otherwise it's hard. Clicking few buttons in hoster panel is much easier."
so we need open source way to do that, coolify/dokploy comes to mind and it exactly do that way
I would say 80% of your point wouldnt be hit at certain scale, as most application grows and therefore outgrow your tech stack. you would replace them anyway at some point
wal archiving is piss easy. you can also just use basebackup. with postgres 17 it is easier than ever with incremental backup feature.
you don't need horizontal scalability when a single server can have 384 cpu real cores, 6TB of ram, some petabytes of pcie5 ssd, 100Gbps NIC.
for tuning postgres parameters, you can start by using pgtune.leopard.in.ua or pgconfig.org.
upgrading major version is piss easy since postgres 10 or so. just a single command.
you do not need pgbouncer if your database adapter library already provide the database pool functionality (most of them do).
for me maintained database also need that same amount of effort, due to shitty documents and garbage user interfaces (all aws, gcp or azure is the same), not to mention they change all the time.