How does KiteSQL performance compare to SQLite?

KiteSQL's TPC-C benchmarks show competitive write speeds, with LMDB backend outperforming RocksDB in some tests, but it's single-threaded and may not match SQLite's broader ecosystem or stability for all use cases.

Can I use KiteSQL in a browser with WebAssembly?

Yes, KiteSQL ships a WebAssembly build for JavaScript runtimes, allowing embedded database functionality in browsers or Node.js, though it requires a localStorage shim for certain features in Node.js.

How to set up schema migrations with KiteSQL ORM?

Use the #[derive(Model)] macro to define typed models, then call database.migrate() to handle common schema updates like adding or renaming columns, keeping migrations close to Rust code instead of manual SQL.

What are the differences between RocksDB and LMDB backends in KiteSQL?

LMDB is optimized for read-heavy workloads with faster performance in benchmarks, while RocksDB handles writes better but may have higher latency; choose based on your application's data access patterns.

Is KiteSQL ACID compliant?

KiteSQL supports transactions and checkpoints for consistency, but ACID properties depend on the storage backend; RocksDB and LMDB provide varying levels of durability and isolation, so review the documentation for specifics.

How to install KiteSQL for Python projects?

Enable the 'python' Cargo feature and use PyO3 bindings; construct the database with Database(path, backend='rocksdb') or in-memory with Database.in_memory(), but note it's less feature-rich than the Rust API.

Open-Awesome

KiteSQL

Apache-2.0Rust

A lightweight embedded relational database for Rust with a native Rust data API, supporting SQL execution and typed ORM.

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734 stars54 forks0 contributors

What is KiteSQL?

KiteSQL is an embedded relational database and native Rust data API designed for embedding directly into applications. It provides both SQL execution and a typed ORM, allowing developers to leverage relational power without relying on external database services. The project supports multiple storage backends and is fully written in Rust for performance and safety.

Target Audience

Rust developers building applications that require an embedded database, such as desktop apps, server-side services, or WebAssembly-based projects needing local data persistence.

Value Proposition

Developers choose KiteSQL for its combination of SQL compatibility and a Rust-native API, offering high write speeds, multiple storage options, and seamless embedding without external dependencies.

Overview

Embedded relational database and native Rust data API.

Use Cases

Best For

Embedding a relational database directly into Rust applications
Building desktop or server applications with local data persistence
Using SQL with a type-safe Rust ORM for data modeling
Developing WebAssembly projects that require an embedded database
Comparing performance between RocksDB and LMDB storage backends
Running TPC-C benchmarks on embedded database engines

Not Ideal For

Distributed systems requiring multi-node clustering or replication
Projects needing full SQL:2016 compliance with advanced features like stored procedures or triggers
High-concurrency server applications where a client-server database is preferred for scalability
Environments where Rust tooling is unavailable, as core features are Rust-centric despite bindings

Pros & Cons

Pros

Embedded and Lightweight

Designed to be embedded directly into applications without external services, reducing infrastructure overhead and simplifying deployment for desktop or server apps.

Rust-Native API

Offers typed ORM models and builder-style queries alongside SQL, providing type safety and an idiomatic experience for Rust developers, as shown in the example code.

Multiple Storage Backends

Supports RocksDB and LMDB for persistent storage, plus in-memory options, allowing performance tuning based on read/write patterns, with benchmarks comparing the two.

WebAssembly Support

Ships a WebAssembly build for use in JavaScript runtimes like Node.js and browsers, extending its reach to web-based projects requiring embedded data persistence.

Cons

Incomplete SQL Compliance

The roadmap mentions SQL 2016 support is not fully implemented, which may limit compatibility with complex queries or migrations from other databases.

Limited Multi-threaded Performance

TPC-C benchmarks are only single-threaded, raising concerns about scalability in high-concurrency environments compared to databases optimized for parallel operations.

Immature Ecosystem

As a newer project, it lacks the extensive tooling, community support, and third-party integrations of established embedded databases like SQLite.

Open Source Alternative To

KiteSQL is an open-source alternative to the following products:

SQLite

Frequently Asked Questions

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