DBX: Lightweight 20MB Database Client for 80+ Databases

Image: GitHub

If you're a developer who constantly switches between MySQL, PostgreSQL, Redis, MongoDB, and various other databases, you've probably grown frustrated juggling multiple clients at the same time. Some require Java, some only work on macOS, and some are a pain to install. DBX solves all of these problems in a single application that weighs just ~20 MB.

DBX is an open-source, Apache-2.0-licensed database client built with Rust and Tauri that supports 80+ databases in one app. It has already reached 15,300+ GitHub stars and boasts 203+ active contributors. Let's dive in!

What is DBX?

DBX is a cross-platform database client designed to be the only tool you need for managing all kinds of databases. Built with Rust (for the backend/native layer) and Vue.js (for the UI), DBX delivers high performance with a remarkably small installer size.

Quick overview:

No Java JRE to install. No Python virtual environment. No bundled Chromium. Just download, install, and connect to your favorite database.

Why DBX Stands Out

1. Tiny Footprint (~20 MB)

This is no joke. DBeaver needs a Java JRE that can eat up hundreds of MB. TablePlus isn't available for Linux. Navicat is paid with a hefty price tag. DBX? Just ~20 MB and it runs right away on macOS, Windows, and Linux with no extra runtime dependencies.

Imagine SSH-ing into a production server and needing a quick query — just download the DBX binary, connect, done. No complicated setup required.

2. Supports 80+ Databases

DBX isn't just for SQL. It supports nearly every type of database out there:

• Relational: MySQL, PostgreSQL, SQLite, MariaDB, SQL Server, Oracle, DB2, Firebird, H2, Access
• NoSQL: MongoDB, Cassandra, HBase
• Analytical: ClickHouse, DuckDB, Doris, StarRocks, TiDB, Snowflake, BigQuery, Redshift, Trino, PrestoSQL
• Time-series: TDengine, InfluxDB, QuestDB, IoTDB, VictoriaMetrics
• Vector: Qdrant, Milvus, Weaviate, ChromaDB
• Search: Elasticsearch, Meilisearch, Easysearch, Manticore
• Key-Value: Redis, etcd, ZooKeeper
• Message Queue: Kafka, Pulsar, RocketMQ, RabbitMQ, MQTT
• Config/Registry: Nacos, Consul
• Graph: Neo4j
• Hybrid: TiDB, OceanBase, CockroachDB, Dolt

And many more — Dameng, GaussDB, openGauss, KingBase, HighGo, and other region-specific databases.

3. Built-in AI

DBX comes with an AI SQL Assistant integrated right into the editor. You can:

• Describe a query in plain English and DBX will generate the SQL for you
• Explain what complex queries do
• Optimize slow-running queries
• Fix SQL errors
• Run AI-generated SQL with built-in safety checks

The AI supports Claude, OpenAI, local models via Ollama, or any other OpenAI-compatible endpoint.

4. Rust Performance

Because it's written in Rust, DBX offers excellent performance:

• Fast startup — no JVM warm-up delays
• Minimal memory footprint
• Native drivers (no JDBC runtime for major databases)
• Virtualized data grid that handles large result sets with ease

Key Features of DBX

1. Desktop GUI (Tauri)

A native desktop application available for all three major platforms:

• macOS — including native title bar support
• Windows — installer and portable options
• Linux — Flatpak or direct download

The UI is modern, supports dark mode, 9 editor themes, and 3 languages (English, 简体中文, Español).

2. Advanced Query Editor

DBX uses CodeMirror 6 as its query editor, packed with features:

-- Automatic syntax highlighting
-- Metadata-aware autocomplete
-- Format SQL with a shortcut
-- Persistent query history
-- Saved SQL snippets
 
-- Try running this query:
SELECT 
    u.id,
    u.name,
    COUNT(o.id) AS total_orders,
    SUM(o.amount) AS total_spent
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
WHERE u.created_at >= '2026-01-01'
GROUP BY u.id, u.name
HAVING COUNT(o.id) > 5
ORDER BY total_spent DESC;

Editor highlights:

• Cmd+Enter to execute a query
• Execute only the highlighted SQL
• Automatic SQL formatting
• Real-time SQL diagnostics
• Persistent query history
• Tab restore — queries survive app restarts
• Run SQL files directly from the file explorer

3. Data Grid (Virtualized)

The data grid in DBX is no ordinary grid. It uses virtualization to handle millions of rows without lag:

• Inline editing — edit cells directly in the grid
• SQL preview — see the query that will run before saving
• WHERE/ORDER BY controls — filter without writing SQL
• DataGrip-style filters — LIKE, NOT LIKE, context filters
• Sorting — click column headers to sort
• Full-text search — search across all data
• Export — to CSV, JSON, Markdown, XLSX, or INSERT statements
• Column resize and auto-fit
• Row numbers and zebra stripes

# Example: export data from the grid to CSV
# Right-click on the data grid > Export As > CSV
# Or use SQL directly:
 
SELECT * FROM products 
WHERE category = 'electronics'
INTO OUTFILE '/tmp/products_export.csv'
FIELDS TERMINATED BY ',' 
ENCLOSED BY '"'
LINES TERMINATED BY '\n';

4. Schema Tools

DBX provides a suite of tools for exploring and managing schemas:

• Schema Browser — navigate databases, schemas, tables, columns, indexes, foreign keys, triggers
• ER Diagram — visualize relationships between tables
• Schema Diff — compare structure between two database connections
• Explain Plan — visualize query execution plans
• Field Lineage — column-level lineage analysis
• Database Search — find objects across schemas
• Table Structure Editor — modify table structure directly from the GUI

-- Example: view table structure in MySQL
DESCRIBE users;
 
-- Example: create a new table
CREATE TABLE analytics_events (
    id BIGINT AUTO_INCREMENT PRIMARY KEY,
    event_type VARCHAR(50) NOT NULL,
    user_id INT,
    payload JSON,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    INDEX idx_event_type (event_type),
    INDEX idx_user_created (user_id, created_at)
);

5. AI SQL Assistant

This is one of DBX's most compelling features. The AI assistant is built directly into the editor, so you don't need to copy-paste queries into a browser to leverage AI:

Example usage:

"Create a query to show the top 10 customers with the highest total spending last month"

The AI will generate:

SELECT 
    c.customer_id,
    c.customer_name,
    c.email,
    SUM(o.amount) AS total_spending
FROM customers c
JOIN orders o ON c.customer_id = o.customer_id
WHERE o.order_date >= DATE_FORMAT(DATE_SUB(NOW(), INTERVAL 1 MONTH), '%Y-%m-01')
  AND o.order_date < DATE_FORMAT(NOW(), '%Y-%m-01')
GROUP BY c.customer_id, c.customer_name, c.email
ORDER BY total_spending DESC
LIMIT 10;

Other AI features:

• Explain query — understand what a complex query does
• Optimize SQL — get performance improvement suggestions
• Fix errors — repair broken SQL
• Safety check — review AI-generated SQL before execution

6. Docker Deployment (Self-Hosted)

DBX can be deployed as a web application using Docker. Perfect for teams that need browser-based database access:

# Deploy with Docker
docker run -d \
  --pull=always \
  --name dbx \
  -p 4224:4224 \
  -v dbx-data:/app/data \
  t8y2/dbx:latest

Or with Docker Compose:

# docker-compose.yml
services:
  dbx:
    image: t8y2/dbx:latest
    pull_policy: always
    ports:
      - "4224:4224"
    volumes:
      - dbx-data:/app/data
    restart: unless-stopped
 
volumes:
  dbx-data:

# Run it
docker compose -f deploy/docker-compose.release.yml up -d

Open http://localhost:4224 in your browser, and you can manage databases from anywhere. Multi-arch images (amd64 / arm64) are available.

7. MCP Server (Model Context Protocol)

DBX provides an MCP server that enables AI coding agents to query databases configured in DBX:

# Install MCP Server
npx @dbx-app/mcp-server

Configure in .mcp.json:

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

The MCP Server is compatible with:

• Claude Code
• Cursor
• Windsurf
• And other MCP-compatible agents

MCP security levels:

• Read Only — can only read data
• Data Read/Write — can read and write data
• Full Access — full access including dangerous operations

8. CLI Tool

For terminal workflows and scripting, DBX provides a CLI:

# Install CLI
npm install -g @dbx-app/cli
 
# Or via Homebrew
brew tap t8y2/tap && brew install dbx-cli
 
# List all connections
dbx connections list --json
 
# Run a query
dbx query local "SELECT 1" --json
 
# Query a specific database
dbx query production "SHOW TABLES" --json

The CLI is especially useful for:

• Automation and scripting
• CI/CD pipelines
• Quick queries from the terminal
• Integration with other tools like Codex

Supported Databases

Here's the complete list of databases supported by DBX, categorized by type:

Relational Database

MySQL, PostgreSQL, MariaDB, SQLite, SQL Server, Oracle, DB2, Firebird, H2, Access, Cloudflare D1, H2, Dolt, RQLite, Turso, CockroachDB

Analytical / OLAP

ClickHouse, DuckDB, Doris, StarRocks, SelectDB, TiDB, Snowflake, BigQuery, Redshift, Trino, PrestoSQL, Hive, Spark, Apache Kyuubi, Apache Impala, Databricks, Databend, Kylin, Vertica, Exasol, Teradata, Cloudberry, OpenTenBase, Manticore Search, Dremio

NoSQL

MongoDB, Cassandra, HBase, Apache Phoenix

Time-Series

TDengine, InfluxDB, VictoriaMetrics, QuestDB, IoTDB, KWDB

Vector Database

Qdrant, Milvus, Weaviate, ChromaDB, Elasticsearch

Search Engine

Elasticsearch, Easysearch, Meilisearch, Manticore

Key-Value

Redis, etcd, ZooKeeper

Config/Registry

Nacos, Consul

Message Queue

Kafka, Pulsar, RocketMQ, RabbitMQ, MQTT

Graph Database

Neo4j

China-specific Databases

Dameng (达梦), GaussDB, openGauss, KingBase, HighGo, UXDB, Vastbase, GoldenDB, YashanDB, SunDB, XuguDB, GBase, OSCAR, TDSQL, PolarDB, GreatSQL

Others

SAP HANA, IRIS, Informix, JDBC (custom)

Installation

macOS (Homebrew)

brew install --cask dbx

Windows (Scoop)

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

Windows (WinGet)

winget install t8y2.dbx

Linux (Flatpak)

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

Manual Download

Download directly from GitHub Releases.

CLI (npm)

npm install -g @dbx-app/cli

CLI (Homebrew)

brew tap t8y2/tap && brew install dbx-cli

How to Use

1. Creating Your First Connection

After installation, open DBX and click New Connection. You'll see a list of supported databases. Choose the database you want to connect to and fill in the connection parameters:

Host: localhost
Port: 3306 (MySQL default)
Username: root
Password: ********
Database: my_app

2. Writing and Running Queries

Open a new tab, write your query, and press Cmd+Enter (macOS) or Ctrl+Enter (Windows/Linux) to execute:

-- Check database version
SELECT VERSION();
 
-- List all tables
SHOW TABLES;
 
-- Query with JOIN
SELECT 
    p.name AS product_name,
    c.name AS category_name,
    p.price
FROM products p
JOIN categories c ON p.category_id = c.id
WHERE p.price > 100000
ORDER BY p.price DESC;

3. Browsing Data

Right-click a table in the schema browser and select Open Table to open the data grid. From there you can:

• View all data
• Filter data by clicking the filter icon
• Sort by clicking column headers
• Edit cells with a double-click
• Export data to various formats

4. Using the AI Assistant

Enable the AI assistant from settings, then use the available shortcut. Or simply highlight the query you want explained and click the AI icon in the toolbar.

5. Deploy via Docker for Teams

# Deploy on server
docker run -d --pull=always --name dbx -p 4224:4224 -v dbx-data:/app/data t8y2/dbx:latest
 
# Team can access via browser
# http://your-server:4224

Comparison vs Other Database Clients

DBX vs DBeaver

Verdict: DBX is lighter and has AI/MCP features that DBeaver lacks. DBeaver is more mature with a larger community.

DBX vs Navicat

Verdict: Navicat is more polished for popular databases, but DBX is free and supports far more database engines.

DBX vs TablePlus

Verdict: TablePlus is more native-feeling on macOS but isn't available on Linux. DBX is free and covers a much broader range of databases.

Use Cases

1. Full-Stack Developers

Need MySQL for the backend, Redis for caching, and MongoDB for NoSQL? DBX handles all of them in one application. No need to install three separate clients.

2. Database Administrators (DBAs)

Schema diff, explain plan, field lineage, and data transfer — all the tools a DBA needs are in DBX. Docker deployment enables access from anywhere.

3. Data Engineers

ClickHouse for OLAP, DuckDB for analytical queries, Kafka for message queues — DBX supports all modern data engineering engines.

4. Teams with AI Workflows

The MCP Server allows AI coding agents like Claude Code or Cursor to directly query databases. One configuration, usable across all AI tools.

5. DevOps / SRE

Quick queries from the terminal via CLI, monitoring Kafka topics, browsing etcd keys, managing ZooKeeper — all from a single tool.

6. Companies with China-specific Databases

DBX has excellent support for databases made in China: Dameng, GaussDB, openGauss, KingBase, HighGo, and more. This is rarely found in other database clients.

Tips and Tricks

Import Connections from DBeaver/Navicat

DBX supports importing connections from DBeaver and Navicat, so you don't have to set everything up from scratch.

SSH Tunnel

DBX supports SSH tunnels with key and password authentication. Perfect for connecting to production databases that are only accessible via SSH.

# Example SSH tunnel via terminal
ssh -L 3306:db-server:3306 user@bastion-host

In DBX, you can configure the SSH tunnel directly in the connection settings.

Color-coded Connections

Assign different colors to each environment (development, staging, production) to avoid accidentally running queries against production.

Encrypted Config Export

Export connections to an encrypted file, then import on another machine. Great for maintaining consistent team setups.

Contributing

DBX is a highly active open-source project with 203+ contributors. If you'd like to contribute:

1. Visit the GitHub repository
2. Read the CONTRIBUTING.md
3. Start with issues labeled good first issue

Conclusion

DBX is one of the most promising database clients of 2026. At just 20 MB, with support for 80+ databases, built-in AI, an MCP Server, CLI, and Docker deployment — it's the Swiss Army Knife for all your database needs.

Key advantages:

• ✅ Lightweight (~20 MB)
• ✅ 80+ databases supported
• ✅ Built-in AI SQL Assistant
• ✅ MCP Server for AI agents
• ✅ Cross-platform (macOS, Windows, Linux)
• ✅ Desktop + Docker + Web
• ✅ CLI for automation
• ✅ Free and open-source (Apache-2.0)

Drawbacks:

• ❌ Still relatively new (less mature than DBeaver)
• ❌ Some features are still under development
• ❌ Documentation could be more comprehensive

If you're looking for a lightweight, fast database client with modern features like AI and MCP, DBX is a must-try. Download it now from dbxio.com or GitHub Releases!

Links:

• 🌐 Homepage: dbxio.com
• 📦 GitHub: github.com/t8y2/dbx
• 📖 Docs: docs
• 💬 Discord: discord.gg/W7NyVDRt6a