You seem to have a rather limited understanding of what kinds of concurrency exist and how those needs are best met. Whether something is a server or not is not very relevant to this discussion.

SQLite is an excellent production db for many real world workloads, as has been widely documented. It is very different to Postgres, so requires learning a whole new skill set.

One way to think about it is that SQLite can work well for the parts of your system where there is naturally strong partitioning.

Sqlite is good for lots of stuff, but you're probably focusing your days on high-scale webapps that want sharding with networked DBs. That's one domain, and an interesting one, but there are lots of others.

I'm a big fan of re-evaluating prior "best practices" in light of technology changes, especially in ways that improve simplicity. Running my family's social media site off a single sqlite DB on a VPS is great. ~15 users, almost zero maintenance. I run my FreshRSS instance off of sqlite, as well as my "now" page. At work, I used sqlite for all kinds of things over the past decades: as an ad hoc job queue, as a quick way to ingest and query lots of logs locally, and present/filter in realtime with simonw's excellent https://github.com/simonw/datasette.

I don't think it's every "sqlite for everything" as much as it is "sqlite in lots of places you probably didn't think to apply it."

kentonv/Cloudflare's work on sqlite at the edge might have made this thinking a bit more popular, but it was always around. https://blog.cloudflare.com/sqlite-in-durable-objects/

I suspect being aware of all those little neat cases and wanting to leverage sqlite for them may be an indicator of experience, rather than the opposite.

There are many cases where SQLite + concurrent front end (like a go net/http server) can handle all the load that a service might ever conceivably have to handle, especially if allowed to scale up hardware over time. You can trivially scale up SQLite to, what, hundreds of thousands of tps?

The only thing you really give up is HA/failover and DR. But there are solutions to deal with those. And single-server systems are generally surprisingly robust (since, in the absence of very complex control planes, uptime goes down with more systems).

That’s why there are billions of SQLite databases right?

SQLite is likely used more than all other database engines combined. Billions and billions of copies of SQLite exist in the wild. SQLite is found in:

Every Android device Every iPhone and iOS device Every Mac Every Windows 10/11 installation Every Firefox, Chrome, and Safari web browser Every instance of Skype Every instance of iTunes Every Dropbox client Every TurboTax and QuickBooks PHP and Python Most television sets and set-top cable boxes Most automotive multimedia systems Countless millions of other applications

https://sqlite.org/mostdeployed.html

Computer science no more get its hands dirty with concrete software than physics primarily being about building bridges.

It is not «a foundational principle of computer science».

Are you one of my enterprise customers? What if your workload does not require write concurrency?

I had very good results giving 1 SQL DB per go routine, so the accesses were serialized up front, on a very high volume (130K requests/second) service. Exact transactionality was not a product goal, and the SQLite was just to backup the in memory state. If we lost a little due to abend or something, that was ok (although for normal maintenance it caught SIGTERM and stopped the listen and then waited for in flight calls and then flushed the remaining changes to SQLite; then on startup it would read the SQLite into memory to populate before taking the listen; persistent storage across container runs, and never both reads and writes to the same file at the same time. (It also just closed the DB and opened a new one when it hit some limit of rows, so as not to fill the disk; the max size of the SQLite corresponded to the max size of the LRU map being served from in memory; then it just flipped A / B between "a full memory worth of data stored" and "the currently updating state." A lot easier than having to write out proto bufs to disk or whatever I would have done for transient (during restarts/maintenance) persistence.

Scale to zero is very useful.

> This is a foundational principle of computer science

How exactly is this a foundational principle of computer science?

It's almost as if Postgres isn't perfect, and one size shoe doesn't fit all.

Some people want some of the benefits you get from SQLite.

SQLite is obviously not perfect, but it's an incredible piece of software, and people regularly find good ways to make use of an excellent pieces of software.

Isn't concurrency also limited by your machines disk speed for writes, what difference does it make if you write sequentially vs concurrently? Why does concurrency even matter for databases?

I worked on an app that had sqlite databases per user... it was fine.

Well if you run a tiny single-threaded app then SQLite is a nice simplification over spinning up a separate machine for Postgres.

How many production apps do you think have enough users to justify these huge DB servers?

I mean - I agree for the typical multi-user, SaaS webapp. But I don't think that's what these folks are proposing. If they are - yeesh, count me out.

If on the other hand they're talking about single-user, software in the small - hell yeah. In fact, I'd also promote DuckDB in this regard (mostly for analytics) - with the power of a single machine these days, you can do a surprising amount and never have to worry about distribution. Unless you know you'll have to, in which case you're probably just digging yourself a hole?

And of course there are now several responses proving your point.

sqlite is more like a file format than a database. it competes with .xlsx.

> "SQLite for everything" crowd is a little bit inexperienced.

every time i see it in a real application, it becomes a huge focus of issues (for example: jellyfin, hermes, openwebui, comfyui)

Sure, SQLite doesn't solve every problem -- but in many cases it solves the need at hand with the reward of one less piece of infra required to support it.

I see obsessions with tooling/solutions constantly from experienced devs who fall in love with the original solution and think it's the only way to do things -- so the experience part cuts both ways.

So teach them. If you want to bring up computer science fundamentals, the question is where does SQLite sit with regards to the CAP theorem. Consistency, Availability, and Partition tolerance. SQLite isn't a distributed system, so there are no partitions to tolerate, so it's a CA system. Other databases make different tradeoffs. For systems that don't need concurrent writes, SQLite is pretty great! There are no users to manage, no permissions, no daemon to run, no server and port to mix up. Just open a file on disk using a library.

I absolutely 100% do not understand it either. At all. Every time I try to over the last year or two I come away with the conclusion its something that sounds cool (to me too!) but is guaranteed to cause more problems than more obvious solutions.

That being said I'd kill for someone who used it and benefited to explain it to me in a practical sense. (specifically where syncing is involved, and syncing a subset of the SQLite is necessary. If it's "just" a document store thats treated like a blob for syncing/backup, that's familiar. If it's all in one storage but only local, that's familiar.)

Re: TFA, I guess it would have helped if I knew what Obelisk was, which is on me, and a more in-depth explanation of how this ties into AI/agents, which is on the industry/writer.