tursodatabase/turso

About

Turso is an in-process SQL database written in Rust, compatible with SQLite. It runs in production today at multiple organizations.

Turso is also a virtual machine. Like SQLite, it compiles SQL into bytecode for that machine, the VDBE, and then runs the bytecode. That design is what lets one engine host more than one SQL dialect. SQLite is the first and primary frontend that compiles to it, and Postgres is now a frontend of its own, with its own dialect and wire protocol. More will follow. Our goal is to be for databases what LLVM is to compilers, with one modern and reliable core, and many frontends compiled down onto it.

How general is that core? General enough to run Doom on it.

See the FAQ for where the project stands on its way to 1.0.

Features and Roadmap

• SQLite compatibility for SQL dialect, file formats, and the C API [see document for details]
• BEGIN CONCURRENT for improved write throughput using multi-version concurrency control (MVCC).
• Change data capture (CDC) for real-time tracking of database changes.
• Multi-language support for
  • Go
  • JavaScript
  • Java
  • .NET
  • Python
  • Rust
  • WebAssembly
• 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 ALTER support and faster schema changes.

The database has the following experimental features:

• Postgres compatibility for SQL dialect and wire protocol, see the see compatibility reference for details.
• Encryption at rest for protecting the data locally.
• Incremental computation using DBSP for incremental view maintenance and query subscriptions.
• Full-Text-Search powered by the awesome tantivy library
• Multi-process WAL coordination via the .tshm sidecar for cross-process WAL readers and writers.

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.

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

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?;

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);

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 get turso.tech/database/tursogo
go install turso.tech/database/tursogo

Example usage:

import (
    "database/sql"
    _ "turso.tech/database/tursogo"
)

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)
}

Example usage:

using Turso;

using var connection = new TursoConnection("Data Source=:memory:");
connection.Open();

connection.ExecuteNonQuery("CREATE TABLE t(a, b)");
var rowsAffected = connection.ExecuteNonQuery("INSERT INTO t(a, b) VALUES (1, 2), (3, 4)");
Console.WriteLine($"RowsAffected: {rowsAffected}");

using var command = connection.CreateCommand();
command.CommandText = "SELECT * FROM t";
using var reader = command.ExecuteReader();
while (reader.Read())
{
    var a = reader.GetInt32(0);
    var b = reader.GetInt32(1);
    Console.WriteLine($"Value1: {a}, Value2: {b}");
}

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.

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

Configuration

Add Turso to your MCP client configuration:

{
  "mcpServers": {
    "turso": {
      "command": "/path/to/.turso/tursodb",
      "args": ["/path/to/your/database.db", "--mcp"]
    }
  }
}

Available Tools

The MCP server provides nine tools for database interaction:

1. open_database - Open a new database
2. current_database - Describe the current database
3. list_tables - List all tables in the database
4. describe_table - Describe the structure of a specific table
5. execute_query - Execute read-only SELECT queries
6. insert_data - Insert new data into tables
7. update_data - Update existing data in tables
8. delete_data - Delete data from tables
9. schema_change - Execute schema modification statements (CREATE TABLE, ALTER TABLE, DROP TABLE)

Once connected, you can ask your AI assistant:

• "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'"

MCP Clients

If you're using Claude Code, you can easily connect to your Turso MCP server using the built-in MCP management commands:

Quick Setup

1. Add the MCP server to Claude Code:

   claude mcp add my-database -- tursodb ./path/to/your/database.db --mcp
   

2. Restart Claude Code to activate the connection

3. 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 command
• tursodb - 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

For Claude Desktop, add the configuration to your claude_desktop_config.json file:

{
  "mcpServers": {
    "turso": {
      "command": "/path/to/.turso/tursodb",
      "args": ["./path/to/your/database.db", "--mcp"]
    }
  }
}

For Cursor, configure MCP in your settings:

1. Open Cursor settings
2. Navigate to Extensions → MCP
3. Add a new server with:
   • Name: turso
   • Command: /path/to/.turso/tursodb
   • Args: ["./path/to/your/database.db", "--mcp"]

Alternatively, you can add it to your Cursor configuration file directly.

Direct JSON-RPC 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 directly:

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

Contributing

We'd love to have you contribute to Turso Database! Please check out the contribution guide to get started.

FAQ

Is Turso Database ready for production use?

Yes — Turso powers production applications today at multiple organizations, including Turso Cloud, the Kin AI assistant, and Spice.ai. Reliability is our top priority: Turso is extensively tested by a collection of tools including a native Deterministic Simulation Testing suite and Antithesis.

That said, we have not yet reached 1.0. The project is under active development, and some features are explicitly marked experimental. Our bar is SQLite-level reliability — one of the most rigorously tested pieces of software in the world — and until we declare 1.0, we recommend the same discipline you would apply to any database: keep independent backups.

How compatible is Turso Database with SQLite?

Turso is compatible with SQLite at the SQL dialect, file format, and C API levels, and existing SQLite database files work as-is. We are not at 100% yet, so some differences are still expected — COMPAT.md tracks the details — but the gap is closing quickly, and full compatibility is a requirement for 1.0.

Is Turso a SQLite database or a Postgres database?

It is one engine with more than one SQL frontend. SQLite is the original and primary frontend, with its dialect, its file format, and its C API, and if that is what you use, nothing changes for you. Postgres is a newer and still experimental frontend that speaks the Postgres dialect and wire protocol. They share everything below the SQL: the storage, the concurrency, the query compiler, and the VM. Postgres is additive.

What do you mean by "the LLVM of databases"?

Like SQLite, Turso compiles a query into bytecode for a virtual machine called the VDBE, and runs that bytecode. SQL is just one language that compiles to it. Our goal is to make that VM a general target, with one modern and rigorously tested core, and many database frontends compiled onto it: SQLite, Postgres, and others over time. LLVM did this for compilers, where a stable intermediate representation let many languages share one backend, and we think databases deserve the same. The bytecode is general enough to run Doom, if you want proof.

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. Both run in production today: libSQL has been battle-tested for longer, while Turso Database is where our development effort is focused and 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]
• Alperen Keles, Ethan Chou, Harrison Goldstein, Leonidas Lampropoulos (2026). DIRT: Database-Integrated Random Testing. In DBTest '26. [PDF]

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!

<a href="https://antithesis.com/"><img src="assets/antithesis.jpg" width="400"></a>

<a href="https://blacksmith.sh"><img src="assets/blacksmith.svg" width="400"></a>

<a href="https://nyrkio.com/"><img src="assets/turso-nyrkio.png" width="400"></a>

Contributors

Thanks to all the contributors to Turso Database!