TimescaleDB VS rust

Don't forget PostgreSQL extensions. For something like a chat log, TimescaleDB (https://www.timescale.com/) can be surprisingly efficient. It will handle partitioning for you, with additional features like data reordering, compression, and retention policies.

Offboard it to Postgres specialists like https://www.timescale.com/

TimescaleDB{:target="_blank"}: an extension of PostgreSQL that adds time-series capabilities to the relational database model. It provides scalability and performance optimizations for handling large volumes of time-stamped data while maintaining the flexibility of a relational database.

Have some experience with https://www.timescale.com in this context

What about getting in touch with commercial organisations that have products/services based on PostgreSQL? For example Timescale, EDB, and Citus Data, or really any hosting provider that offers a managed PostgreSQL service.

There is Timescale.

Friends don't let their friends choose Mysql :)

A super long time ago (decades) when I was using Oracle regularly I had to make a decision on which way to go. Although Mysql then had the mindshare I thought that Postgres was more similar to Oracle, more standards compliant, and more of a real enterprise type of DB. The rumor was also that Postgres was heavier than MySQL. Too many horror stories of lost data (MyIsam), bad transactions (MyIsam lacks transaction integrity), and the number of Mysql gotchas being a really long list influenced me.

In time I actually found out that I had underestimated one of the most important attributes of Postgres that was a huge strength over Mysql: the power of community. Because Postgres has a really superb community that can be found on Libera Chat and elsewhere, and they are very willing to help out, I think Postgres has a huge advantage over Mysql. RhodiumToad [Andrew Gierth] https://github.com/RhodiumToad & davidfetter [David Fetter] https://www.linkedin.com/in/davidfetter are incredibly helpful folks.

I don't know that Postgres' licensing made a huge difference or not but my perception is that there are a ton of 3rd party products based on Postgres but customized to specific DB needs because of the more liberalness of the PG license which is MIT/BSD derived https://www.postgresql.org/about/licence/

Some of the PG based 3rd party DBs:

Enterprise DB https://www.enterprisedb.com/ - general purpose PG with some variants

Greenplum https://greenplum.org/ - Data warehousing

Crunchydata https://www.crunchydata.com/products/hardened-postgres - high security Postgres for regulated environments

Citus https://www.citusdata.com - Distributed DB & Columnar

Timescale https://www.timescale.com/

Why Choose PG today?

If you want better ACID: Postgres

If you want more compliant SQL: Postgres

If you want more customizability to a variety of use-cases: Postgres using a variant

If you want the flexibility of using NOSQL at times: Postgres

If you want more product knowledge reusability for other backend products: Postgres

TimescaleDB is Postgres with extensions to automatically partition tables for fast processing of time series data.

If you haven't dipped your touch-typing fingers into Rust yet, you really owe it to yourself. Rust is a modern programming language with features that make it suitable not only for systems programming -- its original purpose, but just about any other environment, too; there are frameworks that let your build web services, web applications including user interfaces, software for embedded devices, machine learning solutions, and of course, command-line tools. Since a custom GitHub Action is essentially a command-line tool that interacts with the system through files and environment variables, Rust is perfectly suited for that as well.

Here's an example of someone citing a disagreement between CRT and shell32:

https://github.com/rust-lang/rust/issues/44650

This in addition to the Rust CVE mentioned elsewhere in the thread which was rooted in this issue:

https://blog.rust-lang.org/2024/04/09/cve-2024-24576.html

Here are some quick programs to test contrasting approaches. I don't have examples of inputs where they parse differently on hand right now, but I know they exist. This was also a problem that was frequently discussed internally when I worked at MSFT.

    #include 

> instead of choosing a certain numbered version of the random library (if I remember correctly) I let cargo download the latest version which had a completely different API.

Yeah, they didn't follow the instructions and got burned. I still think that multiple things went wrong simultaneously for that experience. I wonder if more prevalent uses of `#[doc(alias = "name")]` being leveraged by https://github.com/rust-lang/rust/pull/120730 (which now that I check only accounts for methods and not functions, I should get on that!) so that when changing APIs around people at least get a slightly better experience.

Almost fixed the compiler: https://github.com/rust-lang/rust/pull/123325

Rust: A secure, efficient, and modern programming language (omitting ten thousand words). You can simply follow the installation instructions provided on the official website.

Recently did something similar in Rust but for generating SVGs. We've adopted it for snapshot testing of cargo and rustc's output. Don't have a good PR handy for showing Github's rendering of changes in the SVG (text, side-by-side, swiping) but https://github.com/rust-lang/rust/pull/121877/files has newly added SVGs.

To see what is supported, see the screenshot in the docs: https://docs.rs/anstyle-svg/latest/anstyle_svg/

We strongly believe in Rust as a powerful language for building production-grade software, especially for systems like ours that run alongside Kubernetes.

The above Assert<{N % 2 == 1}> requires #![feature(generic_const_exprs)] and the nightly toolchain. See https://github.com/rust-lang/rust/issues/76560 for more info.