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

Most Favorite Posts

Judo App - Server Driven UI out of the box

Judo App Judo brings server-driven UI to your iOS and Android apps. Build user interfaces visually in a fraction of time and publish them instantly without submitting to the app store. Build Experiences - With No Code The Judo app for macOS, available through the App Store, is built for design professionals with common keyboard shortcuts and familiar concepts like canvas, layers and inspector panel. Workflow is streamlined with the ability to drag and drop media files directly into your experiences and manage your own Judo files in Finder. Manage Creative Execution A Judo experience is interactive and can include text, images, video and buttons. An experience may be part of a screen, a single screen, or more typically multiple linked screens. Judo supports screen transitions, carousels, horizontal scrolling and modals. Clients can add custom fonts and define global colors and these are updates applied universally. Effortlessly Deploy Judo Cloud syncs your experiences with your iOS and ...

Native Or Web? Bizness Apps Adds HTML5 Platform To Let SMBs Create Their Own Apps — For Both

Bizness Apps’s value proposition is simple: The startup wants to make mobile apps affordable, customizable, and simple to make for the small business owner. Thus, the startup offers a DIY iPhone, iPad, and Android app platform that enables SMBs to create, edit, and manage mobile apps without any programming experience required. You start with a template, customize them to suit your business, and then Bizness Apps makes them native apps and distributes them on iTunes and the Android Marketplace. TechCrunch

Server-driven UI (SDUI): Meet Zalandos AppCraft and AirBnB Lona

A short WTF: Joe Birch:  SERVER DRIVEN UI, PART 1: THE CONCEPT Zalando seems to follow the SDUI principle as well - defining a common design language and construct the screens on the backend while displaying them natively on the clients. They even go one step further; they implemented a mighty toolset to enable non-technical stakeholders to define their own native app screens Compass: Web tooling to create screens and bind data Beetroot: Backend service that combines the screen layout definition with the data Lapis/Golem: iOS/Android UI render engines Crazy cool! Good job, guys (when you do an open-source release?) To even move faster a Flutter based UI render engine implementation was great! See also AirBnB Lona SDUI approach Building a Visual Language Why Dropbox sunsetted its universal C++ mobile project and AirBnB its React Native implementation

Remote Desktop with VNC

Access your Mac from any computer with the use of VNC. This article describes the process of setting up a VNC server on your Mac, and how to access it from afar. Remote Desktop on your Mac for Free VNC Server VNC Client

Measuring a Mobile World: Introducing Mobile App Analytics

Analytics für mobilen App-Traffic ermöglicht durchgängige Messungen entlang des Weges von Kunden innerhalb einer mobilen App. Dazu werden Messwerte in allen Phasen des Kundenkontakts gesammelt – zum Beispiel Akquisitionsmesswerte wie neue/aktive Nutzer, Interaktionsmesswerte wie Besucherfluss, Kundentreue oder App-Abstürze sowie Ergebnismesswerte wie Ziel-Conversions und In-App-Käufe. So hilft Analytics Mobilentwicklern und Marketingexperten, erfolgreichere Apps zu erstellen und bessere Nutzererfahrungen zu schaffen. Die Funktion wird nun Schritt für Schritt eingeführt und gegen Ende des Sommers für alle Nutzer verfügbar sein. Google Analytics Mobile App Analysis