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title: Introducing hyperpb: 10x faster dynamic Protobuf parsing...
description: Buf has released hyperpb, an open-source, fully-dynamic Protobuf parser for Go that is 10x faster than dynamicpb and even 3x faster than statically generated...
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# Introducing hyperpb: 10x faster dynamic Protobuf parsing that’s even 3x faster than generated code · Buf

**[Buf Blog](https://daily.dev/sources/buf)** · 6 min read · 0 upvotes · 0 comments

## Summary

Buf has released hyperpb, an open-source, fully-dynamic Protobuf parser for Go that is 10x faster than dynamicpb and even 3x faster than statically generated Protobuf code, matching or beating vtprotobuf in most benchmarks. It compiles a parser at runtime, using a table-driven, VM-based approach with optional profile-guided optimization for another 50-100% throughput gain. The project was built to solve a bottleneck in Buf's Bufstream product, which requires broker-side, schema-aware validation of Kafka messages, and supports proto2, proto3, and editions-mode schemas.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://buf.build/blog/hyperpb>

## Questions this post answers

### What is hyperpb and how much faster is it than dynamicpb for parsing Protobuf in Go?

hyperpb is a fully-dynamic Protobuf parser for Go released by Buf that is 10x faster than dynamicpb, the standard Go solution for dynamic Protobuf parsing. It is also 3x faster than parsing with statically generated code and matches or beats vtprotobuf's generated code on almost every benchmark, while supporting proto2, proto3, and editions-mode schemas.

_Engineers evaluating Protobuf parsing performance track releases like hyperpb on daily.dev._

### How does hyperpb achieve fast dynamic Protobuf parsing without code generation?

hyperpb compiles a parser at runtime, similar to a regular expression engine, laying out optimized structs per message type to minimize memory use and generating a program for a specialized VM that interprets encoded Protobuf bytes as bytecode. It also supports profile-guided optimization, which tunes the parser to real-time data shapes for an additional 50-100% throughput gain.

_Developers building schema-driven systems can follow runtime parsing techniques like this on daily.dev._

### Why did Buf build hyperpb instead of relying on existing dynamic Protobuf parsers?

Buf needed fast broker-side, schema-aware validation for its Bufstream Kafka product, since existing dynamic parsing like dynamicpb was too slow and resource-intensive to validate incoming Protobuf messages against schemas at scale using Protovalidate. hyperpb was built to close this performance gap so validation could run efficiently on the broker side rather than relying solely on client-side validation.

_Teams weighing client-side versus broker-side data validation strategies can track this tradeoff on daily.dev._

## Similar posts on daily.dev

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---

Tags: [#performance](https://daily.dev/tags/performance), [#backend](https://daily.dev/tags/backend), [#golang](https://daily.dev/tags/golang), [#kafka](https://daily.dev/tags/kafka)

[View this post on daily.dev](https://daily.dev/posts/introducing-hyperpb-10x-faster-dynamic-protobuf-parsing-that-s-even-3x-faster-than-generated-code--3hmmjcmhk)

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