Skip to main content

FlatBuffers instead of JSON (or Protocol Buffers)

FlatBuffers is an efficient cross platform serialization library for C++, Java, C#, Go, Python and JavaScript (C, PHP & Ruby in progress). It was originally created at Google for game development and other performance-critical applications.

Why use FlatBuffers?

  • Access to serialized data without parsing/unpacking - What sets FlatBuffers apart is that it represents hierarchical data in a flat binary buffer in such a way that it can still be accessed directly without parsing/unpacking, while also still supporting data structure evolution (forwards/backwards compatibility).
  • Memory efficiency and speed - The only memory needed to access your data is that of the buffer. It requires 0 additional allocations (in C++, other languages may vary). FlatBuffers is also very suitable for use with mmap (or streaming), requiring only part of the buffer to be in memory. Access is close to the speed of raw struct access with only one extra indirection (a kind of vtable) to allow for format evolution and optional fields. It is aimed at projects where spending time and space (many memory allocations) to be able to access or construct serialized data is undesirable, such as in games or any other performance sensitive applications. See the benchmarks for details.
  • Flexible - Optional fields means not only do you get great forwards and backwards compatibility (increasingly important for long-lived games: don't have to update all data with each new version!). It also means you have a lot of choice in what data you write and what data you don't, and how you design data structures.
  • Tiny code footprint - Small amounts of generated code, and just a single small header as the minimum dependency, which is very easy to integrate. Again, see the benchmark section for details.
  • Strongly typed - Errors happen at compile time rather than manually having to write repetitive and error prone run-time checks. Useful code can be generated for you.
  • Convenient to use - Generated C++ code allows for terse access & construction code. Then there's optional functionality for parsing schemas and JSON-like text representations at runtime efficiently if needed (faster and more memory efficient than other JSON parsers). Java and Go code supports object-reuse. C# has efficient struct based accessors.
  • Cross platform code with no dependencies - C++ code will work with any recent gcc/clang and VS2010. Comes with build files for the tests & samples (Android .mk files, and cmake for all other platforms).
Why not use Protocol Buffers, or .. ?

Protocol Buffers is indeed relatively similar to FlatBuffers, with the primary difference being that FlatBuffers does not need a parsing/ unpacking step to a secondary representation before you can access data, often coupled with per-object memory allocation. The code is an order of magnitude bigger, too. Protocol Buffers has neither optional text import/export nor schema language features like unions.


FlatBuffers on GitHub

Improving Facebook's performance on Android with FlatBuffers
FlatBuffers is a data format that removes the need for data transformation between storage and the UI. In adopting it, we have also driven additional architectural improvements in our app like Flat Models. The mutation extensions that we built on top of FlatBuffers allow us to track server data, mutations, and local state all in a single structure, which has allowed us to simplify our data model and expose a unified API to our UI components.

In last six months, we have transitioned most of Facebook on Android to use FlatBuffers as the storage format. Some performance improvement numbers include:


  • Story load time from disk cache is reduced from 35 ms to 4 ms per story.
  • Transient memory allocations are reduced by 75 percent.
  • Cold start time is improved by 10-15 percent.
  • We have reduced storage size by 15 percent.

FlatBuffersSwift on GitHub
Infrastructure for FlatBuffers, contains a reader and a builder

Comments

Popular posts from this blog

Pattern: Riblets vs. VIPER

Engineering the architecture behind Uber's new rider app

Not being held back by our extensive codebase and previous design choices gave us the freedom where we otherwise would have made compromises. The outcome is the sleek new app you see today, which implements a new mobile architecture across both iOS and Android. Read on to learn why we felt the need to create this new architecture pattern, called Riblets, and how it helps us reach our goals.

The platforms share:

Core architectureClass namesInheritance relationships between business logic unitsHow business logic is dividedPlugin points (names, existence, structure, etc.)Reactive programming chainsUnified platform components
Each Riblet is made up of one Router, Interactor, and Builder with its Component (hence the name), and optional Presenters and Views. The Router and Interactor handle the business logic, while the Presenter and View handle the view logic.

Uber

Stetho - A Chrome debug bridge for Android applications

Stetho is a sophisticated debug bridge for Android applications. When enabled, developers have access to the Chrome Developer Tools feature natively part of the Chrome desktop browser. Developers can also choose to enable the optional dumpapp tool which offers a powerful command-line interface to application internals.

Facebook Github

WireMock

WireMock is a flexible library for stubbing and mocking web services. Unlike general purpose mocking tools it works by creating an actual HTTP server that your code under test can connect to as it would a real web service.

It supports HTTP response stubbing, request verification, proxy/intercept, record/playback of stubs and fault injection, and can be used from within a unit test or deployed into a test environment.

Although it’s written in Java, there’s also a JSON API so you can use it with pretty much any language out there.

WireMock.org