tigerbeetle VS PyOxidizer

I'm waiting for someone to implement the Redis API by swapping out the state machine in TigerBeetle (which was built modularly such that the state machine can be swapped out).

https://tigerbeetle.com/

I fully agree with what Prime says at the end - Joran has really set a new bar here for all future database presentations.

Hearing that the entire TigerBeetle domain logic lives in a single file [0] (and is intended to be pluggable for other OLTP use cases!) makes it 1000% more tempting to spend the weekend getting up to speed with Zig.

[0] https://github.com/tigerbeetle/tigerbeetle/blob/main/src/sta...

Why would you want to build your own accounting ledger from scratch? Accounting is a completely new domain for most engineers, and TigerBeetle (https://tigerbeetle.com/) already solves this problem.

Maelstrom [1], a workbench for learning distributed systems from the creator of Jepsen, includes a simple (model-checked) implementation of Raft and an excellent tutorial on implementing it.

Raft is a simple algorithm, but as others have noted, the original paper includes many correctness details often brushed over in toy implementations. Furthermore, the fallibility of real-world hardware (handling memory/disk corruption and grey failures), the requirements of real-world systems with tight latency SLAs, and a need for things like flexible quorum/dynamic cluster membership make implementing it for production a long and daunting task. The commit history of etcd and hashicorp/raft, likely the two most battle-tested open source implementations of raft that still surface correctness bugs on the regular tell you all you need to know.

The tigerbeetle team talks in detail about the real-world aspects of distributed systems on imperfect hardware/non-abstracted system models, and why they chose viewstamp replication, which predates Paxos but looks more like Raft.

[1]: https://github.com/jepsen-io/maelstrom/

[2]: https://github.com/tigerbeetle/tigerbeetle/blob/main/docs/DE...

> There is no reason to use a memory unsafe language anymore, except legacy codebases, and that is also slowly but surely diminishing. I'm still yet to hear this amazingly compelling reason that you just need memory unsafe languages. In terms of cost/benefits analysis, memory unsafety is literally all costs.

Tell that to the authors of new memory unsafe languages (like Zig) and creators of new project in those languages (like https://tigerbeetle.com) :(

Bundling Python isn't too bad if you find the right tools for it.

I really like https://github.com/indygreg/python-build-standalone and https://github.com/indygreg/PyOxidizer

A bundled, built standalone Python can be 16 to 32MB (including the full standard library, which you can strip down to just the bits you use to save size). Not tiny, but probably not worth switching programming languages over.

But really, I would suggest thinking about what you want to build before "how" or "with which tool" - one of the signs of a person becoming a good engineer is having an array of tools at their disposal and being able to choose a correct tool for the correct task. Rust also excels in integrating with other languages - with JS via WebAssembly (a bit of self-promotion, for example), with Elixir via Rustler, with Python via PyO3 and PyOxidizer, etc. So you absolutely can start writing a frontend app with JS, or a distributed system with Elixir, or a data processing/ML app with Python and use Rust to speed up critical parts of those. Or, in reverse, you can start with Rust & add new capabilities to whatever you're building, that being a frontend, a resilient chat interface, or an ML model.

Thank you, although this is not exactly on topic. I'd not heard of PyOxidizer, but it appears to have the same goal as PyInstaller, py2exe, and cx_Freeze -- as the PyOxidizer readme says, it produces

Here is some example Github Action from PyOxidizer as a Kickstarter: https://github.com/indygreg/PyOxidizer/blob/main/.github/workflows/build-exe.yml

A starting point to try out binary modules by the way would be https://github.com/indygreg/PyOxidizer - could already have benefits by rolling in all dependencies of modules (so no more pip/apt/dnf/... installs on target hosts). Setting this up should be relatively straightforward and could probably be automated enough to even manage to build binary modules for all modules in the community ansible distribution eventually.

PyOxidizer might be another option.

XAR signing is effectively just an RFC 5652 CMS signature plus some minimal data structure manipulation. Code at https://github.com/indygreg/PyOxidizer/blob/faa7dfcea5d66bf5....

Mach-O and bundles, by contrast, require a myriad of additional data structures requiring thousands of lines of code to support. To my knowledge, nobody else has implemented signing of these far-more-complicated primitives. (Existing Mach-O signing solutions just do ad-hoc signing and/or don't handle Mach-O in the context of a bundle.)