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protocolbuffers
protobuf-go
Go2020–2024
protocolbuffers / protobuf-go

protobuf-go

Go support for Google's protocol buffers

5Distinct people
5Mentions
0Explicit recommenders
3.4KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Go support for Google's protocol buffers

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year5 dated mentions

Observed mentions: 2020-03-01 14:59:10 UTC to 2024-05-17 15:45:34 UTC.

0122020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC211
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC202

What Hacker News says

5 sources
Context: I started with proto2 in C++ internal to Google and still use proto3 from some Go and Rust projects over a decade later. I can't say the wire format has ever been a problem for me directly. Newer formats have reduced some CPU overheads, but haven't pulled it all together the way official protobuf and gRPC ecosystems have. From what I've seen the biggest problem with the wire format is that the framing for a nested message requires a varint size. You don't know how many bytes to set aside for that integer until you know how many bytes the nested message will serialize to, and this applies recursively. Without a hacky size cache [1], you get exponential runtime. Even BSON did better here; its nested document framing is fixed-size so it can always go back and patch it later with just an external size stack, no need for an intrusive
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size cache. There are still benefits to the wire format, especially over JSON. For example, you get real 64-bit unsigned integers, and you can disable varint encoding for them (fixed64). It gives you a lot of opportunities for both accuracy and efficiency. The bad news is that normal idiomatic use of protobuf and gRPC infect your code. It's designed for the code to be generated in very predictable standard ways, but those aren't necessarily the ways you actually want. Even if you decide to isolate proto to a corner of your project and use your own model the rest of the time, the transformation between proto types and your own types can cost you more memory allocations and copy more memory instead of sharing existing memory. So if you care about performance, you often have to design a whole project around protobuf end-to-end, infecting your code even more than usual. With JSON in either Go or Rust, you can make your own custom types that serialize to JSON and these types instantly feel and work first-class. You own how the schema is mapped to code; often the only living schema is defined in code anyway. In most cases you can use your own types throughout your project and serialize them to JSON as needed without JSON itself infecting your code. This helps even more if you also involve formats like BSON because they can all coexist just fine for the same types, unlike protobuf which insists on its own types and generated code. Even if you fully embrace protobuf throughout your project, there are other problems and limitations with the generated code. For example, in official protobuf for Go, there's no way to avoid heap allocating each individual nested or repeated message, and there's no way to avoid an absurd 5-machine-word overhead in every single message. (Hopefully will be brought down to 3 soon, but it's been 5 for years). If you're designing a proto schema around these problems, you can seriously compromise readability and maintainability just to work around poor implementation decisions in Go protobuf itself. I'm guilty of that kind of optimization, but when my team saw the benchmarks numbers they agreed it was worth it. This is not the kind of decision you want to have to make in a technical project, but I emphasize that it can still be the right choice in many circumstances. The prost crate for Rust is not official but already gives you more control over your schema. You can technically use your own Rust code instead of the generated code, though I don't see anyone actually do this and it doesn't seem to be encouraged. In any case, my biggest issue with prost is that it makes it difficult (or perhaps currently impossible) to share sub-messages with Arc [2], which on the other hand is trivial with Go just using *. While prost avoids allocations in more cases than Go protobuf, my experience has been that it avoids copies less, and some of those copies require allocations anyway. I'm encouraged that Google's upcoming Rust library seems to be modeled after the C++ one and not the Go one. I haven't seen the latest work on it but I trust it's in a good place given how many collective decades of experience in protobuf implementation are going into it. In summary, for a project that was explicitly designed for efficiency, in practice it can limit your code in ways that hurt efficiency more than they ever helped. And while generating code for many languages is a handy feature, that generated code is unlikely to be what you want, and the more you embrace proto throughout your project the more places you pay efficiency and maintainability tolls. [1] https://github.com/protocolbuffers/protobuf-go/blob/1d4293e0... [2] Not within one message to be sent to a client, because that information would be redundant. More for sharing some nested messages across bigger messages sent to multiple clients.
In Demystifying the protobuf wire format
The benchmark is not comparing apples to apples. prost is the most widely used Protobuf implementation in Rust, maintained by the Tokio organization. prost generates structs and serialization/deserialization code for you. easyproto according to GitHib Search is used only by two projects. easyproto provides primitives for serializing and deserializing Protobuf, and requires hand writing code to do both. A fair comparison would be prost vs google.golang.org/protobuf, or easyproto vs parts of quick-protobuf. In most cases you can make Go as fast as Rust, but from my experience writing performance-sensitive code in Go requires significantly larger time investment and overall requires deeper language expertise. Pebble (RocksDB replacement in Go by CockroachDB) is a good example of this, the codebase is littered with hand-inlined[1] functions,
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hand-unrolled loops and it's not[2] even using Go memory management for performance critical parts, it's using the C memory allocator and manual memory management. [prost]: https://github.com/tokio-rs/prost [easyproto]: https://github.com/VictoriaMetrics/easyproto [google.golang.org/protobuf]: https://github.com/protocolbuffers/protobuf-go [quick-protobuf]: https://github.com/tafia/quick-protobuf [1]: https://github.com/cockroachdb/pebble/blob/c34894c46703fd823... [2]: https://github.com/cockroachdb/pebble/blob/master/docs/memor...
In Fivefold Slower Compared to Go? Optimizing Rust's Protobuf Decoding Performance
I've been working in golang professionally for about a year now coming from a long career in C++. Although there is some simplicity to golang that can be appreciated things like this below make me think that the premise of less is more is fundamentally incorrect if you cannot accomplish everything that is necessary. https://github.com/protocolbuffers/protobuf-go/blob/master/i... Specifically the last one of embedding an empty array of mutexes into a struct prevents that struct from being copied. This is something that is easily and explicitly accomplished in C++ by making the constructors private.
In Less is exponentially more (2012)

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