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SQLite is all you need for durable workflows

obeli.sk

241–250 of 413 posts

Re: SQLite is all you need for durable workflows

#241
post #22

I don't understand this obsession with SQLite for real, production apps. SQLite is an embedded database, completely unsuitable for managing concurrency. This is what database _servers_ are for, e.g., Postgres, MySQL, etc. Their entire job is to allow you to modify data from multiple processes, on different machines, at the same time. This is a foundational principle of computer science. It seems to me that the "SQLit…

Most apps do not actually need the concurrency capacity that Postgres or MySQL are designed for.

Re: SQLite is all you need for durable workflows

#242
post #22

I don't understand this obsession with SQLite for real, production apps. SQLite is an embedded database, completely unsuitable for managing concurrency. This is what database _servers_ are for, e.g., Postgres, MySQL, etc. Their entire job is to allow you to modify data from multiple processes, on different machines, at the same time. This is a foundational principle of computer science. It seems to me that the "SQLit…

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…

I mean... if you count flat files as "databases", there are a heck of a lot more

Re: SQLite is all you need for durable workflows

#243
post #22

I don't understand this obsession with SQLite for real, production apps. SQLite is an embedded database, completely unsuitable for managing concurrency. This is what database _servers_ are for, e.g., Postgres, MySQL, etc. Their entire job is to allow you to modify data from multiple processes, on different machines, at the same time. This is a foundational principle of computer science. It seems to me that the "SQLit…

Thing is SQLite scales better than both those network databases [1] if you're prepared to stick with one big machine (+ a standby). This is even more obvious when you start doing transactions processing an row locks across the network limit you to 1-3k TPS that you cannot scale out of (Pareto distribution is merciless). [1] - https://andersmurphy.com/2025/12/02/100000-tps-over-a-billio...

You know you can host a database like Postgres on the same machine, right?

Re: SQLite is all you need for durable workflows

#244
post #196
post #22

I don't understand this obsession with SQLite for real, production apps. SQLite is an embedded database, completely unsuitable for managing concurrency. This is what database _servers_ are for, e.g., Postgres, MySQL, etc. Their entire job is to allow you to modify data from multiple processes, on different machines, at the same time. This is a foundational principle of computer science. It seems to me that the "SQLit…

there is a difference between concurrency in a distributed environment and concurrency on a single machine across processes. SQLite is incredibly useful for the latter. you seem like the inexperienced one to me..

> you seem like the inexperienced one to me

There is irony here

Re: SQLite is all you need for durable workflows

#245
post #22

I don't understand this obsession with SQLite for real, production apps. SQLite is an embedded database, completely unsuitable for managing concurrency. This is what database _servers_ are for, e.g., Postgres, MySQL, etc. Their entire job is to allow you to modify data from multiple processes, on different machines, at the same time. This is a foundational principle of computer science. It seems to me that the "SQLit…

Thing is SQLite scales better than both those network databases [1] if you're prepared to stick with one big machine (+ a standby). This is even more obvious when you start doing transactions processing an row locks across the network limit you to 1-3k TPS that you cannot scale out of (Pareto distribution is merciless). [1] - https://andersmurphy.com/2025/12/02/100000-tps-over-a-billio...

Wow, what an apples and aliens comparison. You add a bunch of transaction delays to your postgresql case because you can access a database over a network, but you use transaction batching for sqlite? Maybe just compare a local postgresql with/without batching to a local sqlite with/without batching to be much less misleading.

Re: SQLite is all you need for durable workflows

#246
post #84
post #53

Earlier quoted context omitted.

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 cal…

Woof. That sounds very complicated. If you need that kind of write concurrency, use an unlogged table in postgres [0]. Then you don't have to invent a whole sharded thing yourself. [0] https://www.postgresql.org/docs/current/sql-createtable.html...

Running postgresql is an order of magnitude more complicated than sqlite.

130k tps even with unlogged is not always super easy especially if getting hit concurrently. Postgresql connection overhead alone can be pretty brutal if you are setting up and tearing down connections or have 1,000 writers etc.

Postgresql generally requires good network connectivity. Folks doing sqlite distributed tend to have everything independent, you literally don't need to worry about connection / security / firewall / permissioning / internode escape or data leaking etc, can even have problems in local side networking and services can still serve.

Re: SQLite is all you need for durable workflows

#248
post #209

Earlier quoted context omitted.

whats an example of things that you have your agents do that use workflows and sqlite db

Autonomous C to Rust. Automated penetration testing and vuln validation.

you just made me realize how much i wished people stopped talking in abstractions and just stated what they were doing. i hadnt realized how often i saw things like "workflows" and just kinda had my eyes glaze over. none of it ever really clicks until i see the true descriptor of whats going on.

ive been over here using claude relatively simply as of recent, just claude code and i might enter plan mode to do some bigger like scrap together a test suite of some sort, or i just have him scripting and refactoring/reformatting stuff under my direction. i wrote my own cli tool (needed to bake in the snowflake golang driver for external browser sso propagation) and added it as a skill so he can talk to our cloud dbms when im doing analytics things but for the most part its all pretty simple. feel like my productivity is 50x but after over a year with claude ive really backed off on asking him to do insane stuff and mostly keep him churning stuff out for me in domains i know very well.

so i read all this workflow stuff that needs durability and logging and im kind of astounded how many people have their AI stuff just running on their own round the clock. i didn't realize how much of peoples day to days needed to be automated, i don't seem to find myself surrounded by much that should be automated. jira is probably the only thing i need to sit down and automate because its such a translation tax on developers just so business people can feel involved. but outside of that... guess im behind the times, but i dont know if its that. i see the big grand things people use llms for ("im creating the ultimate knowledge base" or "ive automated everything under the sun and im making 10k a week" etc) and i am feeling either too tired, not ambitious enough, or unenthused by the creative and grand ways people are working with AI. seems like everyone has their own "perfect way to use AI" but I can't seem to find the oomph to go beyond using claude as a utility anymore. a year ago (maybe more cant remember anymore its all a blur) with claude in the sonnet era i was so amazed the first thing i did was try to reverse engineer a game using ghidra. had him building test suites to verify the math was correct. we were at this for weeks. my nearby datacenter probably drained 10 lakes. that was just one of _many_ over-ambitious projects i selected because of claude that never saw a finish line.

yesterday i opened beej.us and just started reading. im young and i feel like i somehow went from 'damn this claude shit is pretty cool' to 'AI is whatever its fine' in a year. like the bell curve meme.

Re: SQLite is all you need for durable workflows

#249

I started setting up my workflows using Temporal. It deploys as relatively light weight local app. For an isolated local installation it uses SQLite. It makes the process of dealing with API retries and organizing workflows and tasks really simple. I recommend giving it a try. It is, philosophically, exactly what this article is suggesting, but it adds an incredibly rich and flexible interface for agents to work with…

It sounds like you’re running this mostly on a single machine? Temporal gets much more complex with scale. Cassandra isn’t fun to manage. Ringpop and TChannel are hard to debug when things go wrong. The SQL backend support doesn’t support horizontally scaled replicas (just single instance) due to consistency requirements. Depending on how your code is written, modifying code baked into workflows becomes complex, as a…

Temporal feels massive, I tried it for a small workflow embedded on my system, and worked fine, but when thinking on scaling it, it just didn't made any sense for my use case.

I also have restate.dev on my reseearch list, which on paper should scale well and be definitely more lightweight and simple to setup, worth having a look.

Re: SQLite is all you need for durable workflows

#250

Can’t wait to see the next iteration of this idea with “Logs are all you need for durable workflows.”

Yep. But we all know that one machine can and will fail (or be patched and restarted), so the log needs to be distributed.

Different workflows should probably go in different buckets or "topics" for clarity. Since it's distributed, the system must guarantee that the log items are stored in the same ordering ("offsets") among the nodes.

Not a bad way to do things.

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