compare-go-json VS datasette

jsoniter is json-iterator/go. It is the 3rd column at https://github.com/ohler55/compare-go-json

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.

I've thought about this a lot. I am very confident that the way I use LLMs is both accelerating progress on my core projects (here's a substantial, reviewed PR I landdd just yesterday https://github.com/simonw/datasette/pull/2741) and helping me create plenty of projects that otherwise would not have existed.

I've shipped some features in my largest open source project (Datasette) recently using Claude Code: https://github.com/simonw/datasette/pull/2636

> Has Simon actually produced anything novel or compelling?

Here are some of my recent posts which I self-evaluate as "novel and compelling".

- Running Pydantic’s Monty Rust sandboxed Python subset in WebAssembly https://simonwillison.net/2026/Feb/6/pydantic-monty/ - demonstrating how easy and useful it is to be able to turn Rust code into WASM that can run independently or be used inside a Python wheel for Pyodide in order to provide interactive browser demos of Rust libraries.

- Distributing Go binaries like sqlite-scanner through PyPI using go-to-wheel https://simonwillison.net/2026/Feb/4/distributing-go-binarie... - I think my go-to-wheel utility is really cool, and distributing Go CLIs through PyPI is a neat trick.

- ChatGPT Containers can now run bash, pip/npm install packages, and download files https://simonwillison.net/2026/Jan/26/chatgpt-containers/ - in which I reverse engineered and documented a massive new feature of ChatGPT that OpenAI hadn't announced or documented anywhere

I remain very proud of my current open source projects too - https://datasette.io and https://llm.datasette.io and https://sqlite-utils.datasette.io and a whole lot more: https://github.com/simonw/simonw/blob/main/releases.md

Are you ready to say none of that is "novel or compelling", in good faith?

I've been using LLM-assistance for my larger open source projects - https://github.com/simonw/datasette https://github.com/simonw/llm and https://github.com/simonw/sqlite-utils - for a couple of years now.

Also literally hundreds of smaller plugins and libraries and CLI tools, see https://github.com/simonw?tab=repositories (now at 880 repos) and https://pypi.org/user/simonw/ (340 published packages).

Unlike my tools.simonwillison.net stuff the vast majority of those products are covered by automated tests and usually have comprehensive documentation too.

This combined with something like Datasette¹ would be a really nice toolbox for quickly developing simple database applications.

1. https://datasette.io/