FlatBuffers
| protobuf-flatbuffer-benchmark | FlatBuffers | |
|---|---|---|
| 1 | 48 | |
| 0 | 22,062 | |
| - | 0.6% | |
| 0.0 | 8.7 | |
| over 1 year ago | 4 days ago | |
| Starlark | C++ | |
| - | Apache License 2.0 |
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protobuf-flatbuffer-benchmark
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Faster Protocol Buffers
OK, but I just want readers to be aware that the whole idea that it could take five minutes to parse a million protobufs is completely preposterous. I reimplemented their benchmark just now and it runs at roughly 8 million protos per second, orders of magnitude faster than they state, and I didn't even do anything to optimize it.
https://github.com/jwbee/protobuf-flatbuffer-benchmark
FlatBuffers
- FlatBuffers – an efficient cross platform serialization library for many langs
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Cap'n Proto 1.0
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Cap'n Proto was originally made for https://sandstorm.io/.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-...
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Anyone has experience with reverse engineering flatbuffers?
Much more in the discussion of this particular issue onGitHub: flatbuffers:Reverse engineering #4258
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Flatty - flat message buffers with direct mapping to Rust types without packing/unpacking
Related but not Rust-specific: FlatBuffers, Cap'n Proto.
- flatbuffers - FlatBuffers: Memory Efficient Serialization Library
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How do AAA studios make update-compatible save systems?
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.
- QuickBuffers 1.1 released
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Choosing a protocol for communication between multiple microcontrollers
Or, as an alternative to protobuffers, there's also flatbuffers, which is lighter weight and needs less memory: https://google.github.io/flatbuffers/
- FlatBuffers: FlatBuffers
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Is using Flatbuffers to parse sensor data a bad application of Flatbuffers?
As the title suggests, I am considering using Flatbuffers as a way to parse sensor data that has been stored in local datafiles. The project language is python.
What are some alternatives?
exp-lazyproto - Experimental fast implementation of Protobufs in Go
Protobuf - Protocol Buffers - Google's data interchange format
oteps - OpenTelemetry Enhancement Proposals
MessagePack - MessagePack implementation for C and C++ / msgpack.org[C/C++]
MessagePack - MessagePack serializer implementation for Java / msgpack.org[Java]
Cap'n Proto - Cap'n Proto serialization/RPC system - core tools and C++ library
cereal - A C++11 library for serialization
SBE - Simple Binary Encoding (SBE) - High Performance Message Codec
Kryo - Java binary serialization and cloning: fast, efficient, automatic
Boost.Serialization - Boost.org serialization module
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
Bond - Bond is a cross-platform framework for working with schematized data. It supports cross-language de/serialization and powerful generic mechanisms for efficiently manipulating data. Bond is broadly used at Microsoft in high scale services.