What is the project about?

Project Limbo is a modern evolution of SQLite, built as an in-process OLTP database engine library written in Rust. It aims to be a compatible successor to SQLite, with enhanced features and performance.

What problem does it solve?

It aims to provide a more modern and performant alternative to SQLite, addressing limitations and adding new capabilities while maintaining compatibility. It specifically targets improved concurrency, asynchronous I/O, and extensibility. It also aims to be a better foundation for serverless and edge computing environments.

What are the features of the project?

• Asynchronous I/O: Uses io_uring on Linux for asynchronous operations.
• SQLite Compatibility: Maintains compatibility with SQLite's SQL dialect, file format, and C API.
• Language Bindings: Offers bindings for JavaScript/WebAssembly, Rust, Go, Python, and Java.
• OS Support: Works on Linux, macOS, and Windows.
• Future Features (Roadmap):
  • Integrated vector search.
  • BEGIN CONCURRENT for better write throughput.
  • Improved schema management (better ALTER support, strict column types).

What are the technologies used in the project?

• Rust: The core language.
• io_uring (Linux): For asynchronous I/O.
• SQL: The query language (SQLite dialect).
• WebAssembly (Wasm): For JavaScript bindings.
• C: For compatibility with SQLite's C API and some language bindings.

What are the benefits of the project?

• Modernized SQLite: Brings SQLite into the modern era with features like async I/O.
• Performance: Potentially improved performance due to asynchronous operations and Rust's efficiency.
• Extensibility: Designed for future extensions like vector search.
• Compatibility: Easy migration path from existing SQLite applications.
• Multiple Language Support: Usable from a variety of programming languages.
• Open Source and Community Driven: Encourages contributions and collaboration.

What are the use cases of the project?

• Embedded Databases: Applications needing a local, in-process database (like SQLite).
• Serverless Functions: Suitable for serverless environments due to its lightweight nature and potential for fast startup.
• Edge Computing: Deployable in edge environments where resources are limited.
• Web Applications (via WebAssembly): Can be used directly in web browsers.
• Mobile Applications: Potentially suitable for mobile apps (through language bindings).
• Data-Intensive Applications: Applications that can benefit from asynchronous I/O and improved concurrency.
• Applications Requiring Vector Search: Future use case when vector search is implemented.
• Drop-in Replacement for SQLite: In many cases, it can be used as a direct replacement for SQLite.