### General idea:
(outside of other optimizations made mostly around concurrency):
**When checkpointing, use pages from the PageCache if we can determine
that they are exactly the page/frame that we want.**
e.g. if the frame_cache has an entry:
`Page ID: 104 -> Frame ID's: [1001, 1002]`
and the OngoingCheckpoint has min_frame of 999 and max_frame of 1020, we
should be able to check the PageCache and see if it has page 104, and
only if it is tagged with frame_id = 1002, can we use that page to
backfill the DB file.
Since using a cached page during checkpoint is purely an optimization,
we can be conservative in terms of when we accept that a cached page is
valid to use. I came up with a `wal_tag` which is the frame_id +
checkpoint_seq, which is set only in the two following places:
1. When explicitly reading a frame from the WAL. (inside
Wall::read_frame)
- read_frame is perhaps the most obvious path of ensuring it's the
exact page + frame combination that we want.
2. When appending a frame to the log during the normal process of
writing (during `[Pager::cacheflush]`)
- cacheflush calls append_frame, and inside the Completion, the dirty
flag is cleared, and the wal_tag flag is set to the frame_id.
Inside `finish_read_page` (which is called for every page we read from
either the DB file or WAL.. the `wal_tag` is cleared along with the
`dirty` flag, so that any re-used `PageRef's` don't contain wal_tag's
from any previous or stale pages.
#### **Proposal**:
(In order to merge and simultaneously be able to sleep at night)
there is this debug assertion:
```rust
#[cfg(debug_assertions)]
{
let mut raw = vec![0u8; self.page_size() as usize + WAL_FRAME_HEADER_SIZE];
self.io.wait_for_completion(self.read_frame_raw(target_frame, &mut raw)?)?;
let (_, wal_page) = sqlite3_ondisk::parse_wal_frame_header(&raw);
let cached = cached_page.get_contents().buffer.as_slice();
// while being horrible for performance, we can ensure that the bytes are identical
// when using the cached page vs what we would otherwise have read from disk.
turso_assert!(wal_page == cached, "cache fast-path returned wrong content for page {page_id} frame {target_frame}");
}
```
Performance
=====================================
Average latency for a checkpoint on my local machine:
#### Before: `7-12ms`
#### After: `2-5ms`
Reviewed-by: Nikita Sivukhin (@sivukhin)
Closes #2568
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
- Clone the repository
- Build the library and set your LD_LIBRARY_PATH to include turso's target directory
cargo build --package limbo-go
export LD_LIBRARY_PATH=/path/to/limbo/target/debug:$LD_LIBRARY_PATH
- Use the driver
go get github.com/tursodatabase/turso
go install github.com/tursodatabase/turso
Example usage:
import (
"database/sql"
_ "github.com/tursodatabase/turso"
)
conn, _ = sql.Open("sqlite3", "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!


