FlatBuffers 是一个高效跨平台的C++和Java序列化库，它是Google专为游戏和其它性能要求较高的应用而开发。FlatBuffers 可以让你直接访问序列化后的数据，无需解压并进行解析的过程。同时提供很强的向前和向后兼容性。

FlatBuffers 支持 C++ 和 Java 语言，无需依赖第三方库支持。

为什么使用 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. 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 code supports object-reuse.

• Cross platform C++11/Java code with no dependencies - 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).

项目主页：http://www.open-open.com/lib/view/home/1403059468606