A cross-platform serialization library designed for maximum memory efficiency with zero-copy data access.
FlatBuffers is a cross-platform serialization library that stores data in a compact binary format for maximum memory efficiency. It solves the performance problems of traditional serialization by allowing direct access to serialized data without parsing or unpacking, while maintaining compatibility across different schema versions and programming languages.
Developers building performance-sensitive applications like games, mobile apps, embedded systems, and distributed services that need efficient data serialization and cross-language data exchange.
Developers choose FlatBuffers for its zero-copy access model that eliminates parsing overhead, its minimal memory footprint, and its strong cross-language compatibility—enabling high-performance data exchange between systems written in different programming languages.
FlatBuffers: Memory Efficient Serialization Library
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Enables direct reading of serialized data without parsing overhead, as shown in the C++ and Rust examples, allowing for high-performance data access in latency-sensitive applications.
Uses a compact binary format to minimize memory footprint, making it ideal for mobile apps and embedded systems with strict constraints, per the key features emphasis.
Generates code for 16+ languages including C++, Python, and Rust, facilitating seamless data exchange in polyglot architectures, as listed in the supported languages.
Maintains forwards and backwards compatibility, allowing schema changes without breaking existing data, which is crucial for long-term project maintenance.
Requires building the `flatc` compiler from source using CMake, adding an extra step compared to drop-in serialization libraries, as noted in the Quick Start section.
Changes to data structures necessitate updating .fbs schemas and regenerating code, which can slow iterative development and introduce maintenance overhead.
Uses date-based versioning instead of SemVer, making dependency management and upgrade decisions less predictable, as admitted in the versioning rationale.