foundationdb VS FrameworkBenchmarks

Actually, Apple does this for iCloud! They use FoundationDB[1] to store billions of databases, one for each user (plus shared or global databases).

See: https://read.engineerscodex.com/p/how-apple-built-icloud-to-...

Discussed on HN at the time: https://news.ycombinator.com/item?id=39028672

[1]: https://github.com/apple/foundationdb https://en.wikipedia.org/wiki/FoundationDB

Is this the language in question? https://github.com/apple/foundationdb/blob/main/flow/README....

> I wondered if perhaps this WASM use case for a cross-language library was already just as possible and ergonomic using language bindings and maybe thats why this use case doesnt seem like a big deal to people.

Yeah that’s the reason. You don’t notice it a lot of the time, but FFIs are everywhere already. The most common foreign function interface is basically the ability to call C code, or have functions made available to C code. C is used because everyone knows it and it’s simple. And most languages either compile to native code (eg rust) - which makes linking to C code easy. Or the runtime is implemented in C or C++ (eg V8, Ruby). In languages like that, the standard library is already basically implemented via a FFI to C/C++ code.

I’ve got an iOS app I’m working on that’s half rust and half swift, with a touch of C in the middle. The bindings work great - the whole thing links together into one binary, even with link time optimizations. But the glue code is gross, and when I want to fiddle with the rust to Swift API I need to change my code in about 4 different places.

Most FFIs are a one to many relationship in that if you write a clean C API, you can probably write bindings in every language. But you don’t actually want to call naked C code from Ruby or Javascript. Good bindings will make you forget everything is done via ffi. Eg numpy. I haven’t looked at the wasm component model proposal - I assume it’s trying to make this process cleaner, which sounds lovely.

I maintain the nodejs bindings for foundationdb. Foundationdb bindings are all done via ffi linking to their C code. And the API is complex, using promises and things. I find it really interesting browsing their official bindings to go, Java, Python and Ruby. Same bindings. Same wrapped api. Same team of authors. Just different languages. And that’s enough to make the wrapper wildly different in every language. From memory the Java ffi wrapper is 4x as much code as it is in Ruby.

https://github.com/apple/foundationdb/tree/main/bindings

Isn’t apple server on C/C++?

They have their own db in that

https://github.com/apple/foundationdb

> Any meaningful technology is open source.

Clearly untrue, however FoundationDB is open source, with a permissive license.

https://github.com/apple/foundationdb

So is much of the operational tooling for it:

https://github.com/FoundationDB/fdb-kubernetes-operator

I don't recall any of those details but the test involved injecting a bogus block device that always returns garbage, and noting that this results in garbage records returned from client queries. And I don't think those kinds of issues have been eradicated, browsing through their github issues there are people trying to recover corrupted clusters. https://github.com/apple/foundationdb/issues/2480

For my current job, I have to install FoundationDB (they have a github repo) as a dependency for the project's code.

To clarify, FoundationDB has some documented multi-region features, but it's not at all clear that anybody who runs it at scale relies on those multi-region features [1]. Even if they do, it's not obvious they run this Fearless DR mode at any appreciable latency.

Geo-replication is an area where Anna really shines, and foundation pays severe costs. All of the concurrency control problems have contention footprints on the order of round-trips. Fully optimistic concurrency control needs to expose backoffs quite a few round-trips to be live. Even pessimistic concurrency control requires some number of round trips, probably at least 1.5 optimally, but in practice in most tuned systems, probably 3. A heck of a lot of use cases make sense at 0 global RTTs and don't at 1+. The ability to tell the database how to manage concurrency, and then providing causal is ultimately the best you can do. That's awesome.

At the end of the day, I have to believe that there's a whole big mess of applications we'll build this, on systems in the portion of the design space Anna is choosing, one day. This is only recently not cutting edge research, but it's definitely still research. We don't know how to model these concepts at a high-level and in a composable way where the masses of software developers can engage with them.

It's interesting to think about how long ago we were graced with BAYOU [2], that thing was ahead of its time. I suspect it's going to take a little while longer before these sorts of techniques make their way into data storage primitives we think of as part of the standard vernacular, but I believe we'll get there eventually.

Databases are fun!

[1] https://github.com/apple/foundationdb/wiki/Multi-Region-Repl...

Neat. Thanks for sharing!

Interestingly, may-minihttp is faring very well in the TechEmpower benchmark [1], for whatever those benchmarks are worth. The code is also surprisingly straightforward [2].

[1] https://www.techempower.com/benchmarks/

[2] https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...

ntex was formed after a schism in actix-web and Rust safety/unsafety, with ntex allowing more unsafe code for better performance.

ntex is at the top of the TechEmpower benchmarks, although those benchmarks are not apples-to-apples since each uses its own tricks: https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...

Ruby is slow. Very slow. How much you may ask? https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s... fastest Ruby entry is at 272th place. Sure, top entries tend to have questionable benchmark-golfing implementations, but it gives you a good primer on the overhead imposed by Ruby.

It is also not early 00s anymore, when you pick an interpreted language, you are not getting "better productivity and tooling". In fact, most interpreted languages lag behind other major languages significantly in the form of JS/TS, Python and Ruby suffering from different woes when it comes to package management and publishing. I would say only TS/JS manages to stand apart with being tolerable, and Python sometimes too by a virtue of its popularity and the amount of information out there whenever you need to troubleshoot.

If you liked Go but felt it being a too verbose to your liking, give .NET a try. I am advocating for it here on HN mostly for fun but it is, in fact, highly underappreciated, considered unsexy and boring while it's anything but after a complete change of trajectory in the last 3-5 years. It is actually the* stack people secretly want but simply don't know about because it is bundled together with Java in the public perception.

*productive CLI tooling, high performance, works well in a really wide range of workloads from low to high level, by far the best ORM across all languages and back-end framework that is easier to work with than Node.JS while consuming 0.1x resources

Although that seems to have improved in recent years.

https://www.techempower.com/benchmarks/#hw=ph&test=json§...

RoR and whatever C++ based web backend there is count as a valid comparison in my book. But comparing the languages itself is maybe a bit off.

On a side note, you can actually compare their performance here if you’re really curious. But take it with a grain of salt since these are synthetic benchmarks.

https://www.techempower.com/benchmarks

Most benchmarks you'll find essentially have someone's thumb on the scale (intentionally or unintentionally). Most people won't know the different languages well enough to create comparable implementations and if you let different people create the implementations, cheating happens. The TechEmpower benchmarks aren't bad, but many implementations put their thumb on the scale (https://www.techempower.com/benchmarks). For example, a lot of the Go implementations avoid the GC by pre-allocating/reusing structs or allocate arrays knowing how big they need to be in advance (despite that being against the rules). At some point, it becomes "how many features have you turned off." Some Go http routers (like fasthttp and those built off it like Atreugo and Fiber) aren't actually correct and a lot of people in the Go community discourage their use, but they certainly top the benchmarks. Gin and Echo are usually the ones that are well-respected in the Go community.

There is certainly a lot of speculation in Techempower benchmarks and top entries can utilize questionable techniques like simply writing a byte array literal to output stream instead of constructing a response, or (in the past) DB query coalescing to work around inherent limitations of the DB in case of Fortunes or DB quries.

And yet, the fastest Ruby entry is at 274th place while Rails is at 427th.

https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...

oh what machine? with how many workers? doing what?

search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21

JustJS would like a word https://www.techempower.com/benchmarks/#section=data-r20&tes...

In terms of RPS, this web service is more-or-less the fortunes benchmark in the techempower benchmarks, once the data hits the cache: https://www.techempower.com/benchmarks/#section=data-r21

Or, at least, they would be after applying optimizations to them.

In short, both of these would serve more rps than you will likely ever need on even the lowest end virtual machines. The underlying API provider will probably cut you off from querying them before you run out of RPS.