Protobuf can support zero-copy of strings and byte arrays embedded in the message. Cap'n Proto and FlatBuffers support zero-copy of the entire message structure.
(Disclosure: I'm the author of Cap'n Proto and Protobuf v2.)
My guess are that Flatbuffers are more flexible and slower to read. And 5 years to late to the party.
This HN article, though, is about FlexBuffers. FlexBuffers appears to be based on FlatBuffers, but does not use schemas. Cap'n Proto, FlatBuffers, and Protobuf are all schema-driven (you must define your message types in a special language upfront). FlexBuffers is more like JSON in that all types are dynamic.
Personally I'm a strong believer that schemas are highly desirable, but some people argue that schema-less serializations let you get stuff done faster. I think it's very analogous to the argument between type-safe languages vs. dynamically-typed languages. Obviously there are a lot of smart people on both sides of these arguments.
I haven't looked into exactly how FlexBuffers work but off the top of my head I suspect that leveraging FlatBuffer's "virtual table" technique probably helps here. In (normal, schema-ful) Cap'n Proto, fields within a struct have fixed offset, meaning that unused fields still take space. As I understand it, FlatBuffers tries to avoid this by adding an extra layer of indirection -- each struct has a sort of "virtual table" which stores the offsets of each field, where some fields might not be present at all. If multiple structs in a message happen to end up with the same virtual table, then the virtual table is only written once.
Totally speculating here since, again, I haven't actually looked at FlexBuffers, but if I were building something isomorphic to JSON on top of FlatBuffers, I'd probably look into extending the virtual tables to index fields by name rather than number. So if you have two structures with the same set of field names, they can share a virtual table, and those field names only have to appear once. That'd be a pretty great way to compress JSON.
Back in Cap'n Proto, we don't have these vtables. For data with fixed schemas, my opinion is that these vtables seem like they require more bookkeeping than they are worth. But for dynamic schemas they seem like a much bigger win. So if you wanted to encode dynamic schemas layered on top of Cap'n Proto, you'd probably have to come up with some similar vtable thing yourself.
Funny you should say vtables may not be worth it.. I was of a similar opinion (why would you have many fields that are not in use??) until people showed me some of the Protobuf schemas in use at Google, with hundreds of fields, most unused. This is what pushed me in the direction of the vtable design.
Data always starts out neatly.. but the longer things live, the more this kind of flexibility pays off.
Yeah, I was quite familiar with those back when I was at Google. But, IIRC, a lot of them were semantically unions, but weren't actually marked as such mostly because "oneof" was introduced relatively late in Protobuf's lifetime.
No joke, I originally was arguing for 8-bit vtable entries because surely no-one ever needs more than 256 bytes worth of fields. Good thing my co-workers were smarter than me.
And yes, FlatBuffers has built-in unions from day 1, which was probably helpful.
That article is a bit old; is there anything that stands out to you in the last ~5 years where things have diverged?
For a document database, I don't agree at all. Some time back I spent more time than I'd like developing on Mongo, and boy did I wish I could actually tell it the schema of documents in each collection and have it enforce that (not to mention optimize based on it). A lot of developers actually use libraries on top of Mongo to define and enforce schemas.
I think protocols still don't have the level of tooling that makes it really obvious why schemas are better.
> Personally I'm a strong believer that schemas are highly desirable
I'm currently working on a project that's very executable size sensitive, and having a fixed schema is crucial to that, as can optimize a lot more aggressively. We can even use dead code feedback to identify schema parts that aren't consumed on the client
Just to be clear, even this more limited notion of "zero copy" isn't currently supported in the open-sourced version of protobuf. It is supported in the internal Google version, which is presumably what you're thinking of. There is an open issue [1] tracking the possibility of making it available in the open source version too.