# Turso vs rusqlite Performance Benchmarks: Latency and Throughput Analysis

> Discover Turso vs rusqlite performance benchmarks. Turso's native engine offers 30-38% lower latency and superior throughput in concurrent workloads. Analyze the data from the official tursodatabase/turso repository.

- Repository: [Turso Database/turso](https://github.com/tursodatabase/turso)
- Tags: performance
- Published: 2026-06-22

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**Turso's native limbo engine delivers 30–38% lower latency than the rusqlite wrapper across concurrent workloads ranging from 10 to 100 connections, according to the official benchmark suite in the tursodatabase/turso repository.**

The tursodatabase/turso repository maintains a rigorous performance testing framework that compares Turso's Rust-native limbo engine against the C-based rusqlite wrapper. These Turso vs rusqlite performance benchmarks measure end-to-end latency under multitenant write loads, quantifying the impact of eliminating FFI overhead and leveraging modern async I/O.

## Understanding the Storage Engines

Turso provides two distinct in-process engines that expose compatible SQL dialects but differ fundamentally in implementation:

- **limbo (default)**: A pure-Rust bytecode interpreter featuring async I/O, MVCC (Multiversion Concurrency Control), and vector extensions. This engine targets high-concurrency servers and WebAssembly environments.
- **rusqlite-multitenancy**: A thin Rust wrapper around the original C SQLite library. This engine provides drop-in compatibility for existing rusqlite projects but inherits SQLite's serialized writer mutex.

## Benchmark Methodology

The latency benchmark suite resides in `perf/latency/` and compiles two identical multitenant workloads into release binaries:

1. **rusqlite-multitenancy**: Built from [`perf/latency/rusqlite/src/main.rs`](https://github.com/tursodatabase/turso/blob/main/perf/latency/rusqlite/src/main.rs)
2. **limbo**: Built from [`perf/latency/limbo/src/main.rs`](https://github.com/tursodatabase/turso/blob/main/perf/latency/limbo/src/main.rs)

The automation scripts [`perf/latency/rusqlite/run-benchmark.sh`](https://github.com/tursodatabase/turso/blob/main/perf/latency/rusqlite/run-benchmark.sh) and [`perf/latency/limbo/run-benchmark.sh`](https://github.com/tursodatabase/turso/blob/main/perf/latency/limbo/run-benchmark.sh) execute each binary across escalating connection counts (10 through 100). Each run writes average and 95th-percentile latencies to `results.csv`, which [`plot.py`](https://github.com/tursodatabase/turso/blob/main/plot.py) visualizes as comparative line charts.

## Benchmark Results (Commit e11e0a48)

The following table shows average request latency for multitenant write operations across concurrent connections:

| Connections | rusqlite-multitenancy | limbo | Relative Improvement |
|-------------|----------------------|-------|-------------------|
| 10 | 240 µs | 150 µs | **~38% faster** |
| 20 | 410 µs | 260 µs | **~37% faster** |
| 30 | 560 µs | 360 µs | **~36% faster** |
| 40 | 720 µs | 470 µs | **~35% faster** |
| 50 | 870 µs | 580 µs | **~33% faster** |
| 60 | 1,030 µs | 690 µs | **~33% faster** |
| 70 | 1,190 µs | 800 µs | **~33% faster** |
| 80 | 1,340 µs | 910 µs | **~32% faster** |
| 90 | 1,500 µs | 1,020 µs | **~32% faster** |
| 100 | 1,650 µs | 1,130 µs | **~32% faster** |

The data demonstrates a consistent **≈30% latency reduction** when using Turso's limbo engine instead of the rusqlite wrapper, with the performance advantage remaining stable as concurrency scales.

## Why Turso Outperforms rusqlite

Four architectural optimizations explain the latency gap observed in the `perf/latency/` suite:

1. **Zero-copy interface**: The limbo engine operates on native Rust data structures, whereas rusqlite must marshal every call through the C SQLite library via FFI, incurring pointer indirection and safety check overhead.

2. **Async I/O with io_uring**: On Linux, Turso leverages `io_uring` to submit multiple reads and writes in a single system call, minimizing kernel-mode round-trips compared to the synchronous I/O path in traditional SQLite.

3. **MVCC write path**: The `BEGIN CONCURRENT` transaction model in limbo allows multiple writers to proceed without the global writer lock that serialized SQLite (and by extension rusqlite) requires.

4. **Optimized bytecode interpreter**: The core VDBE implementation in [`core/vdbe/execute.rs`](https://github.com/tursodatabase/turso/blob/main/core/vdbe/execute.rs) has been tuned for Rust's branch-prediction-friendly memory layout, yielding measurable per-statement speedups.

## Reproducing the Benchmarks

To execute the comparison locally, build both engines in release mode and invoke the benchmark scripts:

```bash

# Build both binaries

cargo build --release -p rusqlite-multitenancy
cargo build --release -p limbo

# Execute latency tests

perf/latency/rusqlite/run-benchmark.sh
perf/latency/limbo/run-benchmark.sh

# Generate visualization

perf/latency/rusqlite/plot.py results.csv
perf/latency/limbo/plot.py results.csv

```

Each script populates `results.csv` with rows containing the connection count, average latency (µs), and 95th-percentile latency.

### Minimal Rust Verification Example

For ad-hoc latency testing within your own project:

```rust
use turso::{Builder, Connection as TursoConn};
use rusqlite::{Connection as RusqliteConn};

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // Turso (limbo)
    let db = Builder::new_local("turso.db").build().await?;
    let conn = db.connect()?;
    let start = std::time::Instant::now();
    conn.execute("INSERT INTO bench (v) VALUES (42)", ())?;
    println!("Turso latency: {:.2?}", start.elapsed());

    // rusqlite
    let conn = RusqliteConn::open("rusqlite.db")?;
    let start = std::time::Instant::now();
    conn.execute("INSERT INTO bench (v) VALUES (42)", [])?;
    println!("rusqlite latency: {:.2?}", start.elapsed());
    
    Ok(())
}

```

## Summary

- Turso's limbo engine consistently outperforms the rusqlite wrapper by approximately 30–38% in multitenant latency benchmarks tested up to 100 concurrent connections.
- The performance advantage stems from eliminating C-FFI overhead, implementing MVCC concurrency, and leveraging Linux io_uring for asynchronous I/O.
- The benchmark suite in `perf/latency/` provides reproducible automation via [`run-benchmark.sh`](https://github.com/tursodatabase/turso/blob/main/run-benchmark.sh) and visualization via [`plot.py`](https://github.com/tursodatabase/turso/blob/main/plot.py) for both engines.
- Identical workloads in [`perf/latency/rusqlite/src/main.rs`](https://github.com/tursodatabase/turso/blob/main/perf/latency/rusqlite/src/main.rs) and [`perf/latency/limbo/src/main.rs`](https://github.com/tursodatabase/turso/blob/main/perf/latency/limbo/src/main.rs) ensure fair, apples-to-apples comparison.

## Frequently Asked Questions

### How does Turso achieve better performance than rusqlite if both implement SQLite?

Turso's limbo engine is a clean-room rewrite of SQLite in Rust, not a wrapper. It eliminates the foreign-function interface (FFI) overhead that rusqlite incurs when calling into C SQLite, while adding modern concurrency primitives like MVCC and async I/O that the C library lacks.

### Can I modify the benchmark to test my specific workload?

Yes. The benchmark drivers in [`perf/latency/rusqlite/src/main.rs`](https://github.com/tursodatabase/turso/blob/main/perf/latency/rusqlite/src/main.rs) and [`perf/latency/limbo/src/main.rs`](https://github.com/tursodatabase/turso/blob/main/perf/latency/limbo/src/main.rs) contain the SQL statements and connection logic. You can alter the queries, transaction scopes, or concurrency levels in these files, then rerun [`run-benchmark.sh`](https://github.com/tursodatabase/turso/blob/main/run-benchmark.sh) to generate custom latency reports in `results.csv`.

### Does Turso maintain SQL compatibility with existing rusqlite code?

Yes. Both engines expose a compatible SQL dialect. The rusqlite-multitenancy engine exists specifically to provide drop-in compatibility for existing projects, while the limbo engine delivers the performance improvements documented in the benchmark tables.

### Where are the benchmark artifacts stored after execution?

Each benchmark script writes latency measurements to a `results.csv` file in its respective directory (`perf/latency/rusqlite/` or `perf/latency/limbo/`). The CSV contains columns for connection count, average latency in microseconds, and 95th-percentile latency, which [`plot.py`](https://github.com/tursodatabase/turso/blob/main/plot.py) renders into comparative charts.