I searched using deepwiki how SQLite implements their busy handler. They use a callback system with exponential backoff, where it stores the callback in the pager and in the database. I confess I found this slightly confusing, so I just implemented a simple exponential backoff directly in the `Statement` struct. I imagine SQLite does this in a more convoluted manner, as they do not have a concept of yielding as we do. https://deepwiki.com/search/where-is-the-code-for-the- busy_4a5ed006-4eed-479f-80c3-dd038832831b I also fixed the rust bindings so that it yields when we return `StepResult::IO`, instead of just blocking the async function. To achieve this I implemented the `Stream` trait for `Rows` struct, which unfortunately came with a slight change to the function signature of `rows.next()` to `rows.try_next()`. EDIT: ~test `test_multiple_connections_fuzz` timeouts because now it has the busy handler "slowing" things down (this test generates a lot of busy transactions), so it takes a lot longer for the test to run. Not sure if it is acceptable for us to reduce the number of operations so the test is shorter.~ EDIT: Adjusted the API to be more in line with https://www.sqlite.org/c3ref/busy_timeout.html. Sets maximum total accumulated timeout. If the duration is None or Zero, we unset the busy handler for this Connection. This api defers slightly from SQLite as instead of sleeping for linear amount of time specified by the user, we will sleep in phases until the the total amount of time requested is reached. This means we first sleep of 1ms, then if we still return busy, we sleep for 2 ms, and repeat until a maximum of 100 ms per phase or we reached the total timeout. Example: 1. Set duration to 5ms 2. Step through query -> returns Busy -> sleep/yield for 1 ms 3. Step through query -> returns Busy -> sleep/yield for 2 ms 4. Step through query -> returns Busy -> sleep/yield for 2 ms (totaling 5 ms of sleep) 5. Step through query -> returns Busy -> return Busy to user This slight api change demonstrated a better throughtput in `perf/throughput/turso` benchmark ```sh cargo run -p write-throughput --release -- -t 2 Running write throughput benchmark with 2 threads, 100 batch size, 10 iterations, mode: Legacy Database created at: write_throughput_test.db Thread 1: 1000 inserts in 0.04s (23438.42 inserts/sec) Thread 0: 1000 inserts in 0.08s (12385.64 inserts/sec) === BENCHMARK RESULTS === Total inserts: 2000 Total time: 0.08s Overall throughput: 24762.60 inserts/sec Threads: 2 Batch size: 100 Iterations per thread: 10 Database file exists: true Database file size: 4096 bytes ``` Depends on #3102 Closes #3067 Closes #3074
Turso Database
An in-process SQL database, compatible with SQLite.
About
Turso Database is an in-process SQL database written in Rust, compatible with SQLite.
⚠️ Warning: This software is ALPHA, only use for development, testing, and experimentation. We are working to make it production ready, but do not use it for critical data right now.
Features and Roadmap
- SQLite compatibility for SQL dialect, file formats, and the C API [see document for details]
- Change data capture (CDC) for real-time tracking of database changes.
- Language support for
- Asynchronous I/O support on Linux with
io_uring - Cross-platform support for Linux, macOS, Windows and browsers (through WebAssembly)
- Vector support support including exact search and vector manipulation
- Improved schema management including extended
ALTERsupport and faster schema changes.
The database has the following experimental features:
BEGIN CONCURRENTfor improved write throughput using multi-version concurrency control (MVCC).- Incremental computation using DBSP for incremental view mainatenance and query subscriptions.
The following features are on our current roadmap:
- Vector indexing for fast approximate vector search, similar to libSQL vector search.
Getting Started
Please see the Turso Database Manual for more information.
💻 Command Line
You can install the latest `turso` release with:
curl --proto '=https' --tlsv1.2 -LsSf \
https://github.com/tursodatabase/turso/releases/latest/download/turso_cli-installer.sh | sh
Then launch the interactive shell:
$ tursodb
This will start the Turso interactive shell where you can execute SQL statements:
Turso
Enter ".help" for usage hints.
Connected to a transient in-memory database.
Use ".open FILENAME" to reopen on a persistent database
turso> CREATE TABLE users (id INT, username TEXT);
turso> INSERT INTO users VALUES (1, 'alice');
turso> INSERT INTO users VALUES (2, 'bob');
turso> SELECT * FROM users;
1|alice
2|bob
You can also build and run the latest development version with:
cargo run
If you like docker, we got you covered. Simply run this in the root folder:
make docker-cli-build && \
make docker-cli-run
🦀 Rust
cargo add turso
Example usage:
let db = Builder::new_local("sqlite.db").build().await?;
let conn = db.connect()?;
let res = conn.query("SELECT * FROM users", ()).await?;
✨ JavaScript
npm i @tursodatabase/database
Example usage:
import { connect } from '@tursodatabase/database';
const db = await connect('sqlite.db');
const stmt = db.prepare('SELECT * FROM users');
const users = stmt.all();
console.log(users);
🐍 Python
uv pip install pyturso
Example usage:
import turso
con = turso.connect("sqlite.db")
cur = con.cursor()
res = cur.execute("SELECT * FROM users")
print(res.fetchone())
🦫 Go
go get github.com/tursodatabase/turso-go
go install github.com/tursodatabase/turso-go
Example usage:
import (
"database/sql"
_ "github.com/tursodatabase/turso-go"
)
conn, _ = sql.Open("turso", "sqlite.db")
defer conn.Close()
stmt, _ := conn.Prepare("select * from users")
defer stmt.Close()
rows, _ = stmt.Query()
for rows.Next() {
var id int
var username string
_ := rows.Scan(&id, &username)
fmt.Printf("User: ID: %d, Username: %s\n", id, username)
}
☕️ Java
We integrated Turso Database into JDBC. For detailed instructions on how to use Turso Database with java, please refer to the README.md under bindings/java.
🤖 MCP Server Mode
The Turso CLI includes a built-in Model Context Protocol (MCP) server that allows AI assistants to interact with your databases.
Start the MCP server with:
tursodb your_database.db --mcp
The MCP server provides seven tools for database interaction:
Available Tools
open_database- Open a new databasecurrent_database- Describe the current databaselist_tables- List all tables in the databasedescribe_table- Describe the structure of a specific tableexecute_query- Execute read-only SELECT queriesinsert_data- Insert new data into tablesupdate_data- Update existing data in tablesdelete_data- Delete data from tablesschema_change- Execute schema modification statements (CREATE TABLE, ALTER TABLE, DROP TABLE)
Example Usage
The MCP server runs as a single process that handles multiple JSON-RPC requests over stdin/stdout. Here's how to interact with it:
Example with In-Memory Database
cat << 'EOF' | tursodb --mcp
{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "client", "version": "1.0"}}}
{"jsonrpc": "2.0", "id": 2, "method": "tools/call", "params": {"name": "schema_change", "arguments": {"query": "CREATE TABLE users (id INTEGER, name TEXT, email TEXT)"}}}
{"jsonrpc": "2.0", "id": 3, "method": "tools/call", "params": {"name": "list_tables", "arguments": {}}}
{"jsonrpc": "2.0", "id": 4, "method": "tools/call", "params": {"name": "insert_data", "arguments": {"query": "INSERT INTO users VALUES (1, 'Alice', 'alice@example.com')"}}}
{"jsonrpc": "2.0", "id": 5, "method": "tools/call", "params": {"name": "execute_query", "arguments": {"query": "SELECT * FROM users"}}}
EOF
Example with Existing Database
# Working with an existing database file
cat << 'EOF' | tursodb mydb.db --mcp
{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "client", "version": "1.0"}}}
{"jsonrpc": "2.0", "id": 2, "method": "tools/call", "params": {"name": "list_tables", "arguments": {}}}
EOF
Using with Claude Code
If you're using Claude Code, you can easily connect to your Turso MCP server using the built-in MCP management commands:
Quick Setup
-
Add the MCP server to Claude Code:
claude mcp add my-database -- tursodb ./path/to/your/database.db --mcp -
Restart Claude Code to activate the connection
-
Start querying your database through natural language!
Command Breakdown
claude mcp add my-database -- tursodb ./path/to/your/database.db --mcp
# ↑ ↑ ↑ ↑
# | | | |
# Name | Database path MCP flag
# Separator
my-database- Choose any name for your MCP server--- Required separator between Claude options and your commandtursodb- The Turso database CLI./path/to/your/database.db- Path to your SQLite database file--mcp- Enables MCP server mode
Example Usage
# For a local project database
cd /your/project
claude mcp add my-project-db -- tursodb ./data/app.db --mcp
# For an absolute path
claude mcp add analytics-db -- tursodb /Users/you/databases/analytics.db --mcp
# For a specific project (local scope)
claude mcp add project-db --local -- tursodb ./database.db --mcp
Managing MCP Servers
# List all configured MCP servers
claude mcp list
# Get details about a specific server
claude mcp get my-database
# Remove an MCP server
claude mcp remove my-database
Once configured, you can ask Claude Code to:
- "Show me all tables in the database"
- "What's the schema for the users table?"
- "Find all posts with more than 100 upvotes"
- "Insert a new user with name 'Alice' and email 'alice@example.com'"
Contributing
We'd love to have you contribute to Turso Database! Please check out the contribution guide to get started.
Found a data corruption bug? Get up to $1,000.00
SQLite is loved because it is the most reliable database in the world. The next evolution of SQLite has to match or surpass this level of reliability. Turso is built with Deterministic Simulation Testing from the ground up, and is also tested by Antithesis.
Even during Alpha, if you find a bug that leads to a data corruption and demonstrate how our simulator failed to catch it, you can get up to $1,000.00. As the project matures we will increase the size of the prize, and the scope of the bugs.
More details here.
You can see an example of an awarded case on #2049.
Turso core staff are not eligible.
FAQ
Is Turso Database ready for production use?
Turso Database is currently under heavy development and is not ready for production use.
How is Turso Database different from Turso's libSQL?
Turso Database is a project to build the next evolution of SQLite in Rust, with a strong open contribution focus and features like native async support, vector search, and more. The libSQL project is also an attempt to evolve SQLite in a similar direction, but through a fork rather than a rewrite.
Rewriting SQLite in Rust started as an unassuming experiment, and due to its incredible success, replaces libSQL as our intended direction. At this point, libSQL is production ready, Turso Database is not - although it is evolving rapidly. More details here.
Publications
- Pekka Enberg, Sasu Tarkoma, Jon Crowcroft Ashwin Rao (2024). Serverless Runtime / Database Co-Design With Asynchronous I/O. In EdgeSys ‘24. [PDF]
- Pekka Enberg, Sasu Tarkoma, and Ashwin Rao (2023). Towards Database and Serverless Runtime Co-Design. In CoNEXT-SW ’23. [PDF] [Slides]
License
This project is licensed under the MIT license.
Contribution
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in Turso Database by you, shall be licensed as MIT, without any additional terms or conditions.
Partners
Thanks to all the partners of Turso!
Contributors
Thanks to all the contributors to Turso Database!


