FlatBuffers VS QuickBuffers

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Cap'n Proto was originally made for https://sandstorm.io/.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-...

Much more in the discussion of this particular issue onGitHub: flatbuffers:Reverse engineering #4258

Related but not Rust-specific: FlatBuffers, Cap'n Proto.

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.

Or, as an alternative to protobuffers, there's also flatbuffers, which is lighter weight and needs less memory: https://google.github.io/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.

+1 for Conveyor. We use it for several JavaFX applications, Java CLI tools, and even bundles of native applications (e.g. a C++ protobuf compiler bundled with a GraalVM native image plugin).

The project is currently still limited by a Java 8 runtime, so it's using sun.misc.Unsafe where it makes sense. The code you're looking for is in ByteUtil. It'd be impossible to be competitive with only using byte[] indexing.

In case you are into serialization, I wrote MFL for working with matlab's .mat file format (focuses on providing a nice API around dynamic types), and QuickBuffers as a zero-allocation implementation for Protobuf (contains Java code generation and lots of performance tuning). Both should have a reasonable size to be interesting without being overwhelming.