How to Get Started with FlatBuffers

Updated

To get started with FlatBuffers, write a schema in a .fbs file, compile it with the flatc compiler to generate code for your target language, then build and use that generated code in your application. This path applies if you are working in one of the supported languages (C++, C#, C, Go, Java, Kotlin, JavaScript, Lobster, Lua, TypeScript, PHP, Python, Rust, or Swift) and want direct access to serialized data without a parsing step. The official docs organize this as a Quick Start, a Tutorial, the flatc compiler reference, schema (.fbs) documentation, and per-language guides.

Step 1: Confirm FlatBuffers fits your use case

FlatBuffers is a cross-platform serialization library originally created at Google for game development and other performance-critical applications. It is open source on GitHub under the Apache license v2.0. The docs list four reasons to use it:

  • No parsing/unpacking: you access serialized data directly.
  • Memory efficiency and speed: the only memory needed to access your data is the buffer itself; no heap is required.
  • Backwards and forwards compatibility: the schema can evolve over time while remaining compatible with old buffers.
  • Small footprint: minimal dependencies and a small code footprint.

If your priority is human-readable data or you work mainly in dynamically typed languages with little advance knowledge of the data shape, the docs note JSON is convenient and readable, and FlatBuffers uses JSON as its optional text format. Protocol Buffers is described as relatively similar, with the primary difference being that FlatBuffers skips the parsing/unpacking step to a secondary representation, often coupled with per-object memory allocation.

Step 2: Write a schema (.fbs)

The schema defines your data types and is the input to the compiler. The docs provide a Schema (.fbs) section covering the overview, schema evolution, and grammar. Start with the Quick Start or Tutorial to see a working schema before designing your own; the evolution rules matter if you expect to change the schema after shipping buffers.

Step 3: Compile with flatc

The flatc compiler turns your .fbs schema into generated code for your chosen language. The docs include a dedicated Compiler (flatc) section, including how to build it. The expected result is generated source files you add to your project; the exact flags and output depend on your target language, so follow the compiler reference rather than guessing options.

Step 4: Build and use the generated code

Pick your language guide from the docs: C, C++, C#, Dart, Go, Java, JavaScript, Kotlin, Lobster, Lua, PHP, Python, Rust, Swift, or TypeScript. Each guide covers the language-specific API for reading and writing buffers. There is also a Supported Configurations page for build environment details.

Verify your setup

A working setup produces generated code from flatc without errors, and your application can read data from a buffer without an unpacking step. If generation fails, check the schema against the grammar section and confirm you are using the compiler version that matches your language guide.

Common sticking points

  • Skipping the schema step: the compiler needs a valid .fbs file; the grammar reference is the place to check syntax.
  • Assuming schema changes are free: compatibility is a designed feature, but the evolution rules in the schema section define what is safe.
  • Expecting JSON-like readability: FlatBuffers is binary by default; JSON is only the optional text format.

Where to go next

Beyond the basics, the docs cover FlatBuffers internals, the intermediate representation, annotating buffers (.afb), benchmarks, and FlexBuffers, a schema-less version. These are useful once your first schema and generated code are working.