70+ databases in 20 MB. Desktop, Docker, CLI, built-in AI assistant, and MCP Server.

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Why DBX?

🪶 20 MB, zero runtime bloat No Java JRE. No Python venv. No bundled Chromium. DBX ships as a single small binary — download, install, connect. DBeaver needs Java; TablePlus is macOS-only. DBX runs everywhere with nothing extra.	🤖 AI that lives in your editor Highlight a table, describe what you want, get SQL back — no copy-paste between tools. Works with Claude, OpenAI, or local models via Ollama. Built-in safety checks review AI-generated SQL before it runs.
🔌 MCP: your databases, AI-ready DBX speaks the Model Context Protocol. Claude Code, Cursor, Windsurf, and other AI coding agents can query your databases through connections you already set up. One config, everywhere.	🌐 Desktop + Docker + Web Native app on macOS, Windows, and Linux. Self-host via Docker for team access. Web version for browser-only environments. Same feature set. Same connections.

Features

70+ Databases, One Tool

MySQL, PostgreSQL, SQLite, Cloudflare D1, Redis, MongoDB, DuckDB, ClickHouse, SQL Server, Oracle, Elasticsearch, Easysearch, Qdrant, Milvus, Weaviate, MariaDB, TiDB, OceanBase, openGauss, GaussDB, KWDB, KingBase, Vastbase, GoldenDB, Doris, SelectDB, StarRocks, Manticore Search, Redshift, DM, TDengine, XuguDB, CockroachDB, Access, HighGo, UXDB, and more. Agent/JDBC-oriented profiles extend DBX to H2, Snowflake, Trino, PrestoSQL, Hive, DB2, Informix, Neo4j, Cassandra, BigQuery, Kylin, SunDB, JDBCX, and custom JDBC connections. New native and agent-driven drivers also cover Databricks, SAP HANA, Teradata, Vertica, Firebird, Exasol, YashanDB, GBase 8a/8s, Databend, RQLite, Turso, InfluxDB, QuestDB, IoTDB, etcd, ZooKeeper, Nacos, IRIS, and more. Message queue admin is also available for Pulsar, Kafka, and RocketMQ. All in a single ~20 MB app. No bundled Chromium.

Query Editor

CodeMirror 6 with SQL syntax highlighting, metadata-aware autocomplete, Cmd+Enter execution, selected SQL execution, SQL formatting, diagnostics, and 9 editor themes. Persistent query history, saved SQL snippets, tab restore, and SQL file execution keep repeat work close at hand.

AI SQL Assistant

Describe what you want in plain language — get SQL back. DBX can explain queries, optimize SQL, fix errors, and run AI-generated SQL through built-in safety checks. Works with Claude, OpenAI, local models, or any OpenAI-compatible endpoint.

Data Grid

Virtual-scrolled table that handles large result sets. Inline editing, SQL preview before save, WHERE / ORDER BY controls, DataGrip-style filters, LIKE / NOT LIKE context filters, sorting, full-text search, pagination, column resize, auto-fit, row numbers, zebra stripes, and full cell details. Export or copy as CSV, JSON, Markdown, XLSX, or INSERT statements.

Schema Tools

• Schema browser — databases, schemas, tables, columns, indexes, foreign keys, triggers, with sidebar search & pin
• Object browser — grouped procedures, functions, views, and source editing where supported
• Table structure editor — reviewable column and index changes for supported engines
• ER diagram — visualize table relationships
• Schema diff — compare structures across connections
• Explain plan — visual query execution plan
• Field lineage — column-level lineage analysis
• Database search — find objects across large schemas

Data Operations

• Table import — CSV, Excel
• Data transfer — migrate between databases
• Database export — full database dump
• Data compare — compare table data and review synchronization output
• SQL file execution — run .sql files directly
• File preview — drag & drop Parquet, CSV, JSON to preview instantly (powered by DuckDB)
• Connection import — bring connection profiles from DBeaver or Navicat

Specialized Browsers

• Redis — key pattern search, batch key operations, command runner, TTL editing, and all data types (String, Hash, List, Set, ZSet, Stream)
• MongoDB — document CRUD with pagination, Atlas & replica set URL connection

Safety & Connectivity

SSH tunnel (key & password) · database and AI proxy settings · auto-reconnect on connection loss · confirmation dialogs for destructive operations · encrypted config export/import · color-coded connections · driver store and optional JDBC plugin

Polished UI

Dark mode with native title bar sync · 9 editor themes · English, 简体中文 & Español · layout preferences · built-in auto-update

AI Agent Integration (MCP)

DBX provides a separate Rust-powered MCP server that lets AI coding agents query databases using connections configured in DBX. The MCP server is distributed independently from the desktop application, so installing DBX does not automatically install the MCP executable.

npx @dbx-app/mcp-server

Add to your .mcp.json:

{
  "mcpServers": {
    "dbx": { "command": "npx", "args": ["-y", "@dbx-app/mcp-server"] }
  }
}

Manage the connection allowlist and the Read only, Data read/write, and Full access modes in DBX Settings → MCP. The machine-readable values remain read_only, safe_write, and high_risk_write; client configs do not need permission or connection-scope environment variables.

For upgrade compatibility, an existing DBX_MCP_ALLOW_WRITES=0 (or false) remains a read-only restriction only until a central MCP policy is saved for the first time; it can never enable writes or override a saved policy.

Windows portable builds need DBX_DATA_DIR in the MCP config, pointing to the data directory next to DBX.exe (the folder that contains dbx.db).

For DBX Web or Docker deployments, point the MCP server at the Web backend API. If the Web login page requires a password, set DBX_WEB_PASSWORD to the same password used there:

{
  "mcpServers": {
    "dbx": {
      "command": "npx",
      "args": ["-y", "@dbx-app/mcp-server"],
      "env": {
        "DBX_WEB_URL": "http://localhost:4224",
        "DBX_WEB_PASSWORD": "your-web-login-password"
      }
    }
  }
}

Works with Claude Code, Cursor, Windsurf, and any MCP-compatible agent. Supports listing connections, browsing tables, executing SQL, and opening tables directly in DBX's UI.

Precompiled native binaries are also published for macOS, Linux, and Windows in package releases. They run without Node.js and are suitable for offline or server environments. The npm installation uses the same Rust binary through a small Node.js launcher.

DBX also provides a dedicated CLI package for terminal, script, and Codex workflows:

npm install -g @dbx-app/cli
# or via Homebrew
brew tap t8y2/dbx && brew install dbx-cli
dbx connections list --json
dbx query local "select 1" --json

See the MCP server README and CLI README for details.

Install

Download the latest release from the Releases page.

Homebrew (macOS):

brew install --cask dbx

Scoop (Windows):

scoop bucket add dbx https://github.com/t8y2/scoop-bucket
scoop install dbx

WinGet (Windows):

winget install t8y2.dbx

Flatpak (Linux):

flatpak remote-add --if-not-exists flatpark https://dl.flatpark.org/flatpark.flatpakrepo
flatpak install flatpark com.dbxio.dbx

Updates then arrive through the regular flatpak update. See the DBX page on FlatPark for details.

Self-Hosted (Docker)

DBX provides a web version that can be deployed via Docker. The examples use the latest tag to pull the current release.

docker run -d --pull=always --name dbx -p 4224:4224 -v dbx-data:/app/data t8y2/dbx:latest

This uses the cross-platform dbx-data named volume. Users in China can use the CNB image, docker.cnb.cool/dbxio.com/dbx:latest, for faster pulls.

For Docker Compose, deploy/docker-compose.yml remains the source-build configuration. To deploy a published image, use deploy/docker-compose.release.yml:

docker compose -f deploy/docker-compose.release.yml up -d

services:
  dbx:
    image: t8y2/dbx:latest
    # For faster pulls in China, use the CNB image instead:
    # image: docker.cnb.cool/dbxio.com/dbx:latest
    pull_policy: always
    ports:
      - "4224:4224"
    volumes:
      - dbx-data:/app/data
    restart: unless-stopped

volumes:
  dbx-data:

Open http://localhost:4224 in your browser. Multi-arch images (amd64 / arm64) are available.

To publish DBX under a reverse-proxy context path such as /dbx, set the runtime base path and proxy the same prefix to the container:

environment:
  - DBX_PUBLIC_BASE_PATH=/dbx

When building the frontend yourself with an absolute asset base, set VITE_DBX_BASE_PATH=/dbx/ before pnpm build.

Getting Started

Prerequisites

• Node.js >= 18
• pnpm
• Rust >= 1.88

System Dependencies

macOS:

No additional dependencies required.

Linux (Ubuntu/Debian):

sudo apt-get install -y libwebkit2gtk-4.1-dev libgtk-3-dev libappindicator3-dev librsvg2-dev patchelf libssl-dev

NIXOS/NIX :

See README-NIX.md

Windows:

No additional dependencies required.

Development

make

make installs root dependencies when needed and starts the local Tauri desktop development environment.

Development builds can run alongside an installed DBX instance and share its local data, including connections and history. Avoid changing the same connection or global setting in both windows at once.

[!TIP] DuckDB compilation takes a while. If you're not working on DuckDB features, skip it to speed up local builds:

# Fast checks (skip DuckDB)
make cargo-check-fast
make cargo-test-fast

# Tauri dev without DuckDB
make dev-fast

The --no-default-features flag only affects local development. Release builds (pnpm tauri build) always include DuckDB.

Web version:

make dev-web       # frontend
make dev-backend   # backend

Documentation site:

make docs

The official DBX documentation site lives in docs/. If you want to improve the website content or documentation pages, edit the files under docs/ and run make docs to preview the site locally.

For clean, reproducible local database instances, use the versioned Docker Compose recipes under deploy/database/:

make db-list
make db-verify DB=mysql@8.4

JDBC agent driver development projects live in agents/:

cd agents
./gradlew test

Build artifacts from agents/drivers/<db-type>/build/libs/ are picked up by local driver install flows when available.

Build

make package

The installer will be in src-tauri/target/release/bundle/.

Tech Stack

Layer	Technology
Framework	Tauri 2
Frontend	Vue 3 + TypeScript
UI	shadcn-vue + Tailwind CSS
Editor	CodeMirror 6
Backend	Rust + sqlx / tiberius / redis-rs / mongodb

Documentation

• Official docs — feature guides and tutorials
• Database Test Lab — local database recipes for development and verification
• Contributing — how to pick up issues and open PRs
• Web API reference — HTTP API for Docker/Web deployments
• Examples — CLI, MCP, Docker, and API samples

Community

Support DBX

DBX is free and open source, but ongoing maintenance, database compatibility testing, infrastructure, and release work require sustained time and resources.

Sponsors & Partners

	RainYun is a cloud service provider offering cloud servers, physical servers, game hosting, and developer-friendly infrastructure services.	Visit RainYun
	Qiniu Cloud provides DBX with object storage, CDN, and other cloud infrastructure resources.	Visit Qiniu Cloud
	Easysearch is an enterprise-grade distributed search engine compatible with Elasticsearch APIs, combining full-text, vector, geospatial search, real-time analytics, and AI capabilities in one platform.	Visit Easysearch

• Support DBX — voluntary donations via WeChat or Alipay
• Sponsors & Partners — sponsorship, infrastructure, tools, and community collaboration

FAQ

Is DBX free?

Yes. DBX is open source under Apache-2.0. All features are free.

Does DBX phone home?

No. DBX does not collect telemetry. The auto-update feature checks GitHub Releases for new versions — you can disable it in settings.

Can I use DBX without an internet connection?

Yes. The desktop app works fully offline. For air-gapped driver installs, download offline driver packages from the [Offline Drivers page](https://dbxio.com/en/drivers) on an internet-connected machine, transfer them to the offline machine, then import them in DBX from Settings > Driver Manager. AI features need network access to the model endpoint (or a local model via Ollama).

How is DBX different from DBeaver / TablePlus / Beekeeper Studio?

DBX is 20 MB with no runtime dependencies for its native database features (no system Java or Python required). AI is built into the application, while MCP is provided as a separately installed Rust companion package or native binary. It supports 70+ databases across desktop, Docker, and web from a shared Rust core.

What databases are supported?

MySQL, PostgreSQL, SQLite, Cloudflare D1, Redis, MongoDB, DuckDB, ClickHouse, SQL Server, Oracle, Elasticsearch, Easysearch, Qdrant, Milvus, Weaviate, MariaDB, TiDB, OceanBase, openGauss, GaussDB, KWDB, KingBase, Vastbase, GoldenDB, Doris, SelectDB, StarRocks, Manticore Search, Redshift, DM, TDengine, XuguDB, CockroachDB, Access, HighGo, UXDB, and more. Agent/JDBC-oriented profiles extend support to H2, Snowflake, Trino, PrestoSQL, Hive, DB2, Informix, Neo4j, Cassandra, BigQuery, Kylin, SunDB, JDBCX, Databricks, SAP HANA, Teradata, Vertica, Firebird, Exasol, YashanDB, GBase 8a/8s, Databend, RQLite, Turso, InfluxDB, QuestDB, IoTDB, etcd, ZooKeeper, Nacos, IRIS, and custom JDBC connections. Message queue admin (Pulsar, Kafka, RocketMQ) is also supported.

How do I report a bug or request a feature?

Open an issue on GitHub Issues.

Contributors

Star History

License

Apache-2.0