I do tend to agree that they are bad. I also agree that people put a little too much credence in "came from Google." I can't bring myself to have this much anger towards it. Had to have been something that sparked this.

This is a rage bait, not worth the read.

Despite issues, protobufs solve real problems and (imo) bring more value than cost to a project. In particular, I'd much rather work with protobufs and their generated ser/de than untyped json

So HN, what are the best alternatives available today and why?

Just with those two criteria you’re down to, like, six formats at most, of which Protocol Buffers is the most widely used.

And I know the article says no one uses the backwards compatible stuff but that’s bizarre to me – setting up N clients and a server that use protocol buffers to communicate and then being able to add fields to the schema and then deploy the servers and clients in any order is way nicer than it is with some other formats that force you to babysit deployment order.

The reason why protos suck is because remote procedure calls suck, and protos expose that suckage instead of trying to hide it until you trip on it. I hope the people working on protos, and other alternatives, continue to improve them, but they’re not worse than not using them today.

This sums up a lot of the issues I’ve seen with protobuf as well. It’s not an expressive enough language to be the core data model, yet people use it that way.

In general, if you don’t have extreme network needs, then protobuf seems to cause more harm than good. I’ve watched Go teams spend months of time implementing proto based systems with little to no gain over just REST.

True story: trying to reverse engineer macOS Photos.app sqlite database format to extract human-readable location data from an image.

I eventually figured it out, but it was:

A base64 encoded Binary Plist format with one field containing a ProtoBuffer which contained another protobuffer which contained a unicode string which contained improperly encoded data (for example, U+2013 EN DASH was encoded as \342\200\223)

This could have been a simple JSON string.

The fact that the author is arguing for making all messages required means they don't understand the reasoning for why all fields are optional. This breaks systems (there are are postmortems outlining this) then there are proto mismatches .

I don't actually want to do this, because then you have N + 1 implementations of each data type, where N = number of programming languages touching the data, and + 1 for the proto implementation.

What I personally want to do is use a language-agnostic IDL to describe the types that my programs use. Within Google you can even do things like just store them in the database.

The practical alternative is to use JSON everywhere, possibly with some additional tooling to generate code from a JSON schema. JSON is IMO not as nice to work with. The fact that it's also slower probably doesn't matter to most codebases.

Recently, however, I had the displeasure of working with FlatBuffers. It's worse.

I'm not very upset that protobuf evolved to be slightly more ergonomic. Bolting on features after you build the prototype is how you improve things.

Unfortunately, they really did design themselves into a corner (not unlike python 2). Again, I can't be too upset. They didn't have the benefit of hindsight or other high performance libraries that we have today.

the fact that protobuffers wasn’t immediately relegated to the dustbin shows just how low the bar is for serialization formats.

what alternative do we have? sending json and base64 strings

Most of the other issues in the article can be solved be wrapping things in more messages. Not great, not terrible.

As with the tightly-coupled issues with Go, I'll keep waiting for a better approach any decade now. In the meantime, both tools (for their glaring imperfections) work well enough, solve real business use cases, and have a massive ecosystem moat that makes them easy to work with.

I get the api interoperability between various languages when one wants to build a client with strict schema but in reality, this is more of a theory than real life.

In essence, anyone who subscribes to YAGNI understands that PB and gRPC are a big no-no.

PS: if you need binary format, just use cbor or msgpack. Otherwise the beauty of json is that it human-readable and easily parseable, so even if you lack access to the original schema, you can still EASILY process the data and UNDERSTAND it as well.

If you need to exchange data with other systems that you don't control, a simple format like JSON is vastly superior. You are restricted to handing over tree-like structures. That is a good thing as your consumers will have no problems reading tree-like structures.

It also makes it very simple for each consumer/producer to coerce this data into structs or objects as they please and that make sense to their usage of the data.

You have to validate the data anyhow (you do validate data received by the outside world, do you?), so throwing in coercing is honestly the smallest of your problems.

You only need to touch your data coercion if someone decides to send you data in a different shape. For tree-like structures it is simple to add new things and stay backwards compatible.

Adding a spec on top of your data shapes that can potentially help consumers generate client code is a cherry on top of it and an orthogonal concern.

Making as little assumptions as possible how your consumers deal with your data is a Good Thing(tm) that enabled such useful(still?) things as the WWW.

It's a lesson most people learns the hard way after using PBs for a few months.

It's like how in go most structs don't have a constructor, they just use the 0 value.

Also oneof is made that way so that it is backwards compatible to add a new field and make it a oneof with an existing field. Not everything needs to be pure functional programming.

[1] aidlab.com/aidlab-2

> This puts us in the uncomfortable position of needing to choose between one of three bad alternatives:

I don’t think there is a good system out there that works for both serialization and data models. I’d say it’s a mostly unsolved problem. I think I am happy with protobufs. I know that I have to fight against them contaminating the codebase—basically, your code that uses protobufs is code that directly communicates over raw RPC or directly serializes data to/from storage, and protobufs shouldn’t escape into higher-level code.

But, and this is a big but, you want that anyway. You probably WANT your serialization to be able to evolve independently of your application logic, and the easy way to do that is to use different types for each. You write application logic using types that have all sorts of validation (in the "parse, don't validate" sense) and your serialization layer uses looser validation. This looser validation is nice because you often end up with e.g. buggy code getting shipped that writes invalid data, and if you have a loose serialization layer that just preseves structure (like proto or json), you at least have a good way to munge it into the right shape.

Evolving serialized types has been such a massive pain at a lot of workplaces and the ad-hoc systems I've seen often get pulled into adopting some of the same design choices as protos, like "optional fields everywhere" and "unknown fields are ok". Partly it may be because a lot of ex-Google employees are inevitably hanging around on your team, but partly because some of those design tradeoffs (not ALL of them, just some of them) are really useful long-term, and if you stick around, you may come to the same conclusion.

In the end I mostly want something that's a little more efficient and a little more typed than JSON, and protos fit the bill. I can put my full efforts into safety and the "correct" representation at a different layer, and yes, people will fuck it up and contaminate the code base with protos, but I can fix that or live with it.

I almost burst out in laughter when the article argued that you should reuse types in preference to inlining definitions. If you've ever felt the pain of needing to split something up, you would not be so eager to reuse. In a codebase with a single process, it's pretty trivial to refactor to split things apart; you can make one CL and be done. In a system with persistence and distribution, it's a lot more awkward.

That whole meaning of data vs representation thing. There's fundamentally a truth in the correspondence. As a program evolves, its understanding of its domain increases, and the fidelity of its internal representations increase too, by becoming more specific, more differentiated, more nuanced. But the old data doesn't go away. You don't get to fill in detail for data that was gathered in older times. Sometimes, the referents don't even exist any more. Everything is optional; what was one field may become two fields in the future, with split responsibilities, increased fidelity to the domain.

For messaging, JSON, used in the same way and with the same versioning practices as we have established for evolving schemas in REST APIs, has never failed me.

It seems to me that all these rigid type systems for remote procedure calls introduce more problems that they really solve and bring unnecessary complexity.

Sure, there are tradeoffs with flexible JSONs - but simplicity of it beats the potential advantages we get from systems like Avro or ProtoBuf.

funnily enough, this line alone reveals the author to be an amateur in the problem space they are writing so confidently about.

At some stage with every ESP or Arduino project, I want to send and receive data, i.e. telemetry and control messages. A lot of people use ad-hoc protocols or HTTP/JSON, but I decided to try the nanopb library. I ended up with a relatively neat solution that just uses UDP packets. For my purposes a single packet has plenty of space, and I can easily extend this approach in the future. I know I'm not the first person to do this but I'll probably keep using protobufs until something better comes along, because the ecosystem exists and I can focus on the stuff I consider to be fun.

Nearly every other complaint is solved by wrapping things in messages (sorry, product types). Don't get the enum limitation on map keys, that complaint is fair.

Protobuf eliminates truckloads of stupid serialization/deserialization code that, in my embedded world, almost always has to be hand-written otherwise. If there was a tool that automatically spat out matching C, Kotlin, and Swift parsers from CDDL, I'd certainly give it a shot.

Protobuf as a language feels clunky. The “type before identifier” syntax looks ancient and Java-esque.

The tools are clunky too. protoc is full of gotchas, and for something as simple as validation, you need to add a zillion plugins and memorize their invocation flags.

From tooling to workflow to generated code, it’s full of Google-isms and can be awkward to use at times.

That said, the serialization format is solid, and the backward-compatibility paradigms are genuinely useful. Buf adds some niceties to the tooling and makes it more tolerable. There’s nothing else that solves all the problems Protobuf solves.

Chances are, the author literally used software that does it as he wrote these words. This feature is critical to how Chrome Sync works. You wouldn’t want to lose synced state if you use an older browser version on another device that doesn’t recognize the unknown fields and silently drops them. This is so important that at some point Chrome literally forked protobuf library so that unknown fields are preserved even if you are using protobuf lite mode.

I haven't used these very seriously but a problem I had a while back was that that the wire format was not what the applications wanted to use, but a good application format was to space-inefficient for wire.

As far as I could see there was not a great way to do this. You could rewrite wire<->app converter in every app, or have a converter program and now you essentially have two wire formats and need to put this extra program and data movement into workflows, or write a library and maintain bindings for all your languages.