Jussi Saurio fb31fd56ba Merge 'Simulator: refactor and simplify InteractionPlan' from Pedro Muniz
Depends on #3775 - to remove noise from this PR.
## Motivation
In my continued efforts in making the simulator more accessible and
simpler to work with, I have over time simplified and optimized some
parts of the codebase like query generation and decision making so that
more people from the community can contribute and enhance the simulator.
This PR is one more step in that direction.
Before this PR, our `InteractionPlan` stored `Vec<Interactions>`.
`Interactions` are a higher level collection that will generate a list
of `Interaction` (yes I know the naming can be slightly confusing
sometimes. Maybe we can change it later as well. Especially because
`Interactions` are mainly just `Property`). However, this architecture
imposed a problem when MVCC enters the picture. MVCC requires us to make
sure that DDL statements are executed serially. To avoid adding even
more complexity to plan generation, I opted on previous PRs to check
before emitting an `Interaction` for execution, if the interaction is a
DDL statement, and if it is, I emit a `Commit` for each connection still
in a transaction. This worked slightly fine, but as we do not store the
actual execution of interactions in the interaction plan, only the
higher level `Interactions`, this meant that I had to do some
workarounds to modify the `Interactions` inside the plan to persist the
`Commit` I generated on demand.
## Problem
However, I was stupid and overlooked the fact that for certain
properties that allow queries to be generated in the middle (referenced
as extensional queries in the code), we cannot specify the connection
that should execute that query, meaning if a DDL statement occurred
there, the simulator could emit the query but could not save it properly
in the plan to reproduce in shrinking. So to correct and make
interaction generation/emission less brittle, I refactored the
`InteractionPlan` so that it stores `Vec<Interaction>` instead.
## Implications
- `Interaction` is not currently serializable using `Serde` due to the
fact that it stores a function in `Assertion`. This means that we cannot
serialize the plan into a `plan.json`. Which to me is honestly fine, as
the only things that used `plan.json` was `--load` and `--watch`
options. Which are options almost nobody really used.
- For load, instead of generating the whole plan it just read the plan
from disk. The workaround for that right now is just load the `cli_opts`
that were last run for that particular seed and use those exact options
to run the simulation.
- For watch, currently there is not workaround but, @alpaylan told me
has some plans to make assertions serializable by embedding a custom
language into the `plan.sql` file, meaning we will probably not need a
json file at all to store the interaction plan. And this embedded
language will make it much easier to bring back a more proper watch
mode.
- The current shrinking algorithms all have some notion of properties
and removal of properties, but `Interaction` do not have this concept.
So I added some metadata to interactions and a origin ID to each
`Interaction` so that we can search through the list of interactions
using binary search to get all of the interactions that are part of the
same `Property`. To support this, I added an `InteractionBuilder` and
some utilities to iterate and remove properties in the `InteractionPlan`
## Conclusion
Overall, this code simplifies emission of interactions and ensures the
`InteractionPlan` always stores the actual interactions that get
executed. This also decouples more query generation logic from query
emission logic.

Closes #3774
2025-11-19 11:10:51 +02:00
2025-08-08 15:45:05 +04:00
2025-11-13 01:16:09 +02:00
2025-09-27 14:13:45 -04:00
2025-11-19 09:40:08 +02:00
2025-11-03 16:40:18 +04:00
2025-10-06 18:19:22 +04:00
2025-09-24 18:06:55 -03:00
2025-03-29 14:46:11 +02:00
2025-11-17 11:45:02 -03:00
2025-10-20 23:48:19 -05:00
2025-01-14 18:37:26 +02:00
2025-04-15 12:45:46 -03:00
2025-11-19 09:40:08 +02:00
2025-10-30 18:15:59 +02:00
2025-07-30 11:45:24 +02:00
2025-11-01 07:16:32 +01:00
2025-10-30 11:38:56 +02:00
2024-07-12 13:07:34 -07:00
2024-07-12 12:38:56 -07:00
2025-11-02 10:46:54 +02:00

Turso Database

Turso Database

An in-process SQL database, compatible with SQLite.

Crate NPM PyPI Maven Central

Chat with the Core Developers on Discord

Chat with other users of Turso (and Turso Cloud) on Discord


About

Turso Database is an in-process SQL database written in Rust, compatible with SQLite.

⚠️ Warning: This software is in BETA. It may still contain bugs and unexpected behavior. Use caution with production data and ensure you have backups.

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.
  • Multi-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 ALTER support and faster schema changes.

The database has the following experimental features:

  • BEGIN CONCURRENT for improved write throughput using multi-version concurrency control (MVCC).
  • Encryption at rest for protecting the data locally.
  • Incremental computation using DBSP for incremental view mainatenance and query subscriptions.

The following features are on our current roadmap:

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

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

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

  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
Claude Desktop

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.db", "--mcp"]
    }
  }
}
Cursor

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.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.

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.

List of rewarded cases:

  • B-Tree interior cell replacement issue in btrees with depth >=3 (#2106)
  • Don't allow autovacuum to be flipped on non-empty databases (#3830)

More details here.

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!

Description
No description provided
Readme 43 MiB
Languages
Rust 76.8%
Tcl 6.6%
C 6.4%
Dart 2.4%
Java 2.3%
Other 5.3%