ungoogled-chromium-archlinux VS logica

There is a working patch for 103 now.

You can build Ungoogled Chromium from the AUR or get a binary through the OBS repository by following the steps here

I've never run into any codec issue using either the AUR version or the one compiled by GitHub Actions or OBS which are all linked here. If you have a problem with those please open an issue and I'll look into it

In this case, there are repos with precompiled binaries for Ungoogled Chromium, like the Chaotic AUR and OBS: https://github.com/ungoogled-software/ungoogled-chromium-archlinux/releases

I assume you're using Manjaro, so it should be in the AUR, or you can get a custom repo with prebuilt binaries here.

There was a recent update to the flags in makepkg.conf that cause build failures: https://github.com/ungoogled-software/ungoogled-chromium-archlinux/issues/123

Prebuilt Arch binaries exist here: https://github.com/ungoogled-software/ungoogled-chromium-archlinux#ungoogled-chromium-archlinux

Or, just download binaries that are approved by the source

If you're interested in this I would also recommend you check out Logica[0], which is a datalog-like language that is explicitly made to compile to SQL queries.

0: https://logica.dev/

> I guess the intention is to be better than SQL but then I was left with "under which circumstances?"

Excellent question.

Two of the most common use cases for databases are "transactional processing" (manipulating small numbers of rows in real time) and "analytical processing" (querying enormous numbers of rows, typically in a read-only fashion).

SQL is generally fine for transactional workloads.

But analytical queries sometimes involve multi-page queries, with lots of JOINs and CTEs. And these queries are often automatically generated.

And once you start writing actual multi-page "programs" in SQL, you may decide that it's a fairly clunky and miserable programming language. What Datalog typically buys you is a way to cleanly decompose large queries into "subroutines." And it offers a simpler syntax for many kinds of complex JOINs.

Unfortunately, there isn't really a standard dialect of Datalog, or even a particular dialect with mainstream traction. So choosing Datalog is a bit of a tradeoff: does it buy you enough, for your use case, that it's worth being a bit outside the mainstream? Maybe! But I'd love to see something like Logica gain more traction: https://logica.dev/

Interesting; a Google engineer previously published a Datalog variant for BigQuery: https://logica.dev/

This new language seems similar to differential-Datalog (which is sadly in maintenance mode): https://news.ycombinator.com/item?id=33521561

Looks pretty cool. I'd be interested if the README had a comparison with Google's Logica (https://github.com/EvgSkv/logica)

Oh wow that is neat!

And yes, this kind of thing is why datalog is a lot more amenable to fast query plans & runtimes than prolog. This part is especially cool: https://github.com/EvgSkv/logica/blob/main/compiler/dialects...

Google new programming Language that compiles to SQL (Support BigQuery and Postgres) feels very exciting. Blog: https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html Github: https://github.com/EvgSkv/logica

Going to be? It already is. In fact, one thing the article misses is right there at the bottom of the project page: