FlatBuffers VS Cap'n Proto

According to the official website:

> Protobuf is intentionally designed to NOT require any parsing at all.

As others have mentioned, this is simply not the case, and the VARINT encoding is a trivial counterexample.

It is this required decoding/parsing that (largely) distinguishes protobuf from Google's flatbuffers:

https://github.com/google/flatbuffers

https://flatbuffers.dev/

Cap'n Proto (developed by Kenton Varda, the former Google engineer who, while at Google, re-wrote/refactored Google's protobuf to later open source it as the library we all know today) is another example of zero-copy (de)serialization.

I don't work at Cloudflare but follow their work and occasionally work on performance sensitive projects.

If I had to guess, they looked at the landscape a bit like I do and regarded Cap'n Proto, flatbuffers, SBE, etc. as being in one category apart from other data formats like Avro, protobuf, and the like.

So once you're committed to record'ish shaped (rather than columnar like Parquet) data that has an upfront parse time of zero (nominally, there could be marshalling if you transmogrify the field values on read), the list gets pretty short.

https://capnproto.org/news/2014-06-17-capnproto-flatbuffers-... goes into some of the trade-offs here.

Cap'n Proto was originally made for https://sandstorm.io/. That work (which Kenton has presumably done at Cloudflare since he's been employed there) eventually turned into Cloudflare workers.

Another consideration: https://github.com/google/flatbuffers/issues/2#issuecomment-...

Much more in the discussion of this particular issue onGitHub: flatbuffers:Reverse engineering #4258

Related but not Rust-specific: FlatBuffers, Cap'n Proto.

If json files are a concern because of space, you can always look into something like protobuffers or flatbuffers. But whatever you use, you should try to find a solution where you don't have to think about the actual serialization/deserialization of your objects, and can just concentrate on the data.

Or, as an alternative to protobuffers, there's also flatbuffers, which is lighter weight and needs less memory: https://google.github.io/flatbuffers/

To be fair, if that's what you need ProtoBuf isn't the only option. Cap'n Proto[1], JSON Schema[2], or any other well supported message-definition language could probably achieve that as well, each with their own positives and negatives.

[1]: https://capnproto.org/

[2]: https://json-schema.org/

Yeah I pretty much only use my own alternate container implementations (from KJ[0]), which avoid these footguns, but the result is everyone complains our project is written in Kenton-Language rather than C++ and there's no Stack Overflow for it and we can't hire engineers who know how to write it... oops.

[0] https://github.com/capnproto/capnproto/blob/v2/kjdoc/tour.md

- may massively reduce the latency involved.

Those sharing Cap'n Proto-encoded data may have particular interest. Cap'n Proto (https://capnproto.org) is fantastic at its core task - in-place serialization with zero-copy - and we wanted to make the IPC (inter-process communication) involving capnp-serialized messages be zero-copy, end-to-end.

That said, we paid equal attention to other varieties of payload; it's not limited to capnp-encoded messages. For example there is painless (<-- I hope!) zero-copy transmission of arbitrary combinations of STL-compliant native C++ data structures.

To help determine whether Flow-IPC is relevant to you we wrote an intro blog post. It works through an example, summarizes the available features, and has some performance results. https://www.linode.com/blog/open-source/flow-ipc-introductio...

Of course there's nothing wrong with going straight to the GitHub link and getting into the README and docs.

Currently Flow-IPC is for Linux. (macOS/ARM64 and Windows support could follow soon, depending on demand/contributions.)

FWIW, my C++ toolkit library, KJ, does the same thing.[0]

But presumably you could still write a condition predicate which looks at things which aren't actually part of the mutex-wrapped structure? Or does is the Rust type system able to enforce that the callback can only consider the mutex-wrapped value and values that are constant over the lifetime of the wait? (You need the latter e.g. if you are waiting for the mutex-wrapped value to compare equal to some local variable...)

[0] https://github.com/capnproto/capnproto/blob/e6ad6f919aeb381b...

The second one is to encode data in such a way that you can read it and operate on it directly from the buffer. You write data in a layout that is the same, or easily transformed as types in memory. To do that you usually need to encode with a known schema, only Sized types to efficiently compute fields locations as offsets in the buffer, and you usually represent pointers as offset into the encode. You can look at capnproto protocol for instance https://capnproto.org/

Worked well for Cap'n Proto (the cerealization protocol)! https://capnproto.org/

With all due respect, you read completely wrong.

* The very first use case for which Cap'n Proto was designed was to be the protocol that Sandstorm.io used to talk between sandbox and supervisor -- an explicitly adversarial security scenario.

* The documentation explicitly calls out how implementations should manage resource exhaustion problems like deep recursion depth (stack overflow risk).

* The implementation has been fuzz-tested multiple ways, including as part of Google's oss-fuzz.

* When there are security bugs, I issue advisories like this:

https://github.com/capnproto/capnproto/tree/v2/security-advi...

* The primary aim of the entire project is to be a Capability-Based Security RPC protocol.