tigerbeetle VS PyOxidizer

Indeed!

I was so glad to see you cite not only the Rebello paper but also Protocol-Aware Recovery for Consensus-Based Storage. When I read your first comment, I was about to reply to mention PAR, and then saw you had saved me the trouble!

UW-Madison are truly the vanguard where consensus hits the disk.

We implemented Protocol-Aware Recovery for TigerBeetle [1], and I did a talk recently at the Recurse Center diving into PAR, talking about the intersection of global consensus protocol and local storage engine. It's called Let's Remix Distributed Database Design! [2] and owes the big ideas to UW-Madison.

[1] https://github.com/coilhq/tigerbeetle

[2] https://www.youtube.com/watch?v=rNmZZLant9o

> It sounds like payments might be part of the larger concept of declarative programming (DP)

Yes, exactly! The idea with TigerBeetle's state machine [1] is to expose double-entry accounting as higher level financial primitives, so that developers can think in terms of declaring transfers from one account to another. The business logic behind the scenes is detailed, but the interfaces and data structures are simple.

[1] https://github.com/coilhq/tigerbeetle/blob/main/src/state_ma...

> Maybe TigerBeetle could be generalized to support any multi-step distributed process?

That's part of the plan, that the distributed database framework of TigerBeetle can be used as a ”distributed Iron Man suit” to support any kind of state machine.

It's a pleasure. Let me know if you have any more questions about TigerBeetle. Our design doc is also here: https://github.com/coilhq/tigerbeetle/blob/main/docs/DESIGN....

Surprisingly, some of the most powerful distributed systems algorithms or tools are actually deterministic. They're powerful because they can "load the dice" and so make the distributed system more intuitive for humans to reason about, more resilient to real world network faults, and do all this with more performance.

For example, Barbara Liskov and James Cowling's deterministic view change [1], which isn't plagued by the latency issues of RAFT's randomized dueling leader problem. Viewstamped Replication Revisited's deterministic view change can react to a failed primary much quicker than RAFT (heartbeat timeouts don't require randomized "padding" as they do in RAFT), commence the leader election, and also ensure that the leader election succeeds without a split vote.

Determinism makes all that possible.

Deterministic testing [2][3] is also your best friend when it comes to testing distributed systems.

[1] I did a talk on VSR, including the benefits of the view change — https://www.youtube.com/watch?v=Wii1LX_ltIs

[2] FoundationDB are pioneers of deterministic testing — https://www.youtube.com/watch?v=OJb8A6h9jQQ

[3] TigerBeetle's deterministic simulation tests — https://github.com/coilhq/tigerbeetle#simulation-tests

This is the chasm problem, where people don't use a technology because people aren't using that technology, thus the technology has difficulty gaining adoption. I did see that Zig does have it's own killer app and startup that's using Zig: TigerBeattle.

Control flow statements should always be on their own lines, then it's easy to find all of them by visually scanning top-down, without needing to look all the way down each line.

[1]: https://github.com/coilhq/tigerbeetle/blob/main/src/vsr/repl...

> In hindsight, data logic should be in the database itself.

This is the reason we are creating TigerBeetle [1] at Coil, as an open source distributed financial accounting database, with the double entry logic and financial invariants enforced through financial primitives within the database itself.

This is all the more critical for financial data, because raw data consistency is not enough for financial transactions, you also need financial consistency, not to mention immutability.

The performance of doing it this way is also easier. For example, around a million financial transactions per second on commodity hardware, with p100 latency around 10-20ms.

[1] https://github.com/coilhq/tigerbeetle

You probably already know this — because we’ve mentioned it a few times — but Coil champions and supports open-source projects and is privacy-first, by default. Over the years, Developer Relations at Coil has championed and sponsored teams that write Open Web Documentations and projects that empower open-source developers to get paid. Coil has also incubated many open-source projects like Tigerbeetle and Rafiki.

[6] Partial logical sector reads/writes even when using O_DIRECT — https://github.com/coilhq/tigerbeetle/blob/main/src/storage....

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.)