Live Database ERD Generators

ChartDB is a database schema visualizer and entity-relationship diagramming platform designed to help developers understand, design, and document complex data architectures. It functions as a visual workspace where users can create and modify database schemas, define table attributes, and map foreign key relationships. By parsing database metadata or SQL scripts, the tool generates interactive diagrams that provide a clear overview of structural interdependencies and data associations. The platform distinguishes itself through its focus on automated documentation and schema synchronization. It supports programmatic diagram generation and scheduled background tasks that refresh visual representations to reflect changes in the underlying database structure. This ensures that technical documentation remains aligned with the live schema, while features like dependency mapping and relationship cardinality visualization provide deeper insights into how data entities interact. Beyond visualization, the tool facilitates schema portability by converting diagrams into standard database markup scripts, enabling version control and migration across different environments. Users can manage their workspace through automated layout engines, grid alignment, and filtering tools, or export diagrams as images for stakeholder sharing. The platform also supports embedding interactive diagrams into external documentation and offers containerized self-hosting options for teams requiring private infrastructure and data sovereignty.

django-extensions is a specialized toolset for the Django framework providing utilities for database visualization, application debugging, development environment management, and custom management command execution. It functions as a collection of tools designed to automate development tasks and inspect the internal state of an application. The project provides a database visualization tool for generating diagrams of data models and comparing schemas to map complex relationships. It also includes a debugging utility to intercept email traffic and audit user permissions to troubleshoot application behavior. The toolset covers a broad range of diagnostic capabilities, including the auditing of URL routing patterns, the validation of template syntax, and the management of database migration snapshots. It further enhances the development workflow through an interactive shell and an extended suite of management commands.

Chat2DB is an AI-powered SQL client and multi-database GUI manager designed for managing various relational and NoSQL database systems. It serves as a visual database management tool and a natural language to SQL interface, allowing users to convert plain text descriptions into executable and optimized queries. The platform distinguishes itself through automated business intelligence capabilities, which include the generation of real-time data visualization dashboards and AI-driven data analysis from spreadsheets. To ensure data privacy, it supports secure local AI deployment, enabling large language models to run on-premises so that sensitive metadata is not uploaded to external servers. Broadly, the project covers database administration, visual schema design with entity-relationship diagramming, and data management utilities such as migration assistants and synthetic test data generation. It also provides team collaboration features, including role-based access control and workspace synchronization. The software supports flexible deployment as either a standalone local desktop application or a centralized web-based server.

Beekeeper Studio is a cross-platform desktop application designed for database management and SQL development. It provides a unified graphical interface to connect to, query, and modify data across a wide range of relational and NoSQL database systems. The application functions as a comprehensive workspace, integrating tools for schema design, record editing, and data visualization. The project distinguishes itself through a focus on secure, flexible connectivity and AI-assisted workflows. It supports advanced authentication methods, including enterprise single sign-on, multi-factor authentication, and token-based access, alongside secure traffic routing via SSH tunneling and SSL encryption. Users can leverage AI-driven query generation to translate natural language into executable SQL, while the interface allows for direct, spreadsheet-like data editing and transactional staging to ensure data integrity. The platform covers a broad capability surface, including robust import and export management, schema inspection, and visual entity relationship diagram generation. It also offers extensive customization options, such as editor behavior settings, native extension loading for SQLite, and third-party add-on integration. The application is distributed as a native desktop installer for Windows, Linux, and MacOS, with support for portable execution and offline-only operation modes.

Mathesar is a no-code database manager and PostgreSQL GUI that provides a visual interface for managing relational database structures and records. It functions as a low-code data platform for administering schemas, tables, and relationships without the need to write manual SQL commands. The platform allows for the creation of shareable forms to collect data and the management of file attachments linked directly to database records. It includes a PostgreSQL administration tool for controlling database roles, user permissions, and data validation rules. The system covers relational data modeling and visual database management, enabling users to link tables and query data through a visual builder. It provides capabilities for importing and exporting data, formatting column displays, and managing record associations via a spreadsheet-like interface.

DrawDB is a browser-based visual database modeler designed for creating, organizing, and documenting relational database schemas. It provides an interactive interface for drag-and-drop entity relationship mapping, allowing users to plan and visualize complex data architectures through a centralized workspace. The platform distinguishes itself by enabling real-time collaborative design, allowing teams to iterate on schemas while maintaining a single source of truth. It functions entirely on the client side, utilizing local memory for state management and saving data directly to the local file system or browser storage. This approach ensures offline functionality and user privacy by eliminating the need for backend database dependencies. Beyond visual modeling, the tool includes automated SQL script generation to convert diagrams into executable code for various database systems. It also supports standardized data serialization, enabling users to export and import designs for compatibility with external migration tools. The interface utilizes canvas-based rendering to maintain performance during the manipulation of complex diagrams.

Prisma is a database toolkit that provides a unified access layer for interacting with relational and document databases. It centers on a declarative schema modeling approach, where developers define their data structures in a human-readable language. This schema serves as the single source of truth, from which the toolkit automatically generates type-safe database clients that provide compile-time validation and editor autocomplete for all data operations. The project distinguishes itself through a high-performance, Rust-based query engine that handles query planning and connection pooling outside the application runtime. It further streamlines development by offering introspection-based synchronization, which updates the local data model by scanning existing database structures. Additionally, it includes a visual database explorer that allows developers to inspect records, navigate relational diagrams, and manage data configurations directly within their development environment or a web-based interface. Beyond core data access, the toolkit supports a range of operational workflows including automated database testing through isolated instance provisioning and performance optimization via integrated query analysis. The ecosystem is extensible through middleware for query interception and various generators that facilitate schema documentation and integration with other development tools.

SQLiteStudio is an open-source graphical tool for browsing, editing, and managing SQLite database files. It combines a full-featured SQL editor with syntax highlighting, a visual database schema designer for creating entity-relationship diagrams, and a plugin-based extensibility platform that allows adding custom functionality through C/C++, JavaScript, Tcl, or Python. The application distinguishes itself through its multi-language scripting engine, which embeds JavaScript, Tcl, and Python interpreters to enable user-defined functions and scripts within SQL queries. It supports encrypted database access using multiple cipher formats, drag-and-drop SQL generation for creating SELECT or UPDATE statements, and a grid-based data editing interface with inline cell editing, filtering, and selective commit or rollback of changes. The MDI document management system organizes database windows for simultaneous editing, while the plugin architecture allows extending core functionality through shared libraries. Beyond its core database management capabilities, SQLiteStudio provides comprehensive data import and export across formats including CSV, JSON, XML, HTML, SQL, and PDF. It includes tools for data population with test data generation, cross-table string search, and cross-database object copying or moving. The SQL editor offers automatic code completion, continuous syntax analysis, query history browsing, and SQL formatting with configurable options. Users can also load external SQLite extension libraries and create custom collation sequences or SQL functions.

Atlas is a SQL database schema management tool and database infrastructure as code framework. It provides a declarative database migration engine that computes the difference between a desired schema state and the current database state to automatically generate the necessary SQL for transitions. The project distinguishes itself through a comprehensive suite of analysis and visualization tools, including a database schema linter that detects destructive changes and data loss risks. It also features a SQL schema visualization tool capable of generating entity-relationship diagrams from extracted database structures. The platform covers a broad surface of database operations, including versioned migration management, schema drift detection, and declarative seed data synchronization. It extends into security and governance by treating database access control, roles, and permissions as version-controlled code. The tool integrates with CI/CD pipelines, GitOps workflows, and infrastructure orchestration tools to automate the linting, testing, and deployment of database changes.

PostGraphile is an automated tool that converts a PostgreSQL database schema into a fully functional GraphQL API. It serves as a GraphQL execution engine and schema orchestrator, utilizing database schema introspection to retrieve strongly typed metadata directly from PostgreSQL. The project features a modular system for composing and standardizing GraphQL schemas through plugins, which manage naming conventions and connections. It includes a PostgreSQL query builder that constructs dynamic, SQL-injection-proof queries using tagged template literals. The system employs a declarative query planning engine to optimize request processing and reduce server load. Additionally, it provides a mechanism to export dynamically generated in-memory schemas into standalone JavaScript source code.

DBeaver is a universal database client and administration environment designed for managing diverse relational and non-relational database systems. It provides a unified graphical interface that enables users to perform data manipulation, schema migration, and performance monitoring across multiple platforms. By utilizing a standardized driver abstraction layer, the application translates generic requests into database-specific commands, ensuring consistent interaction regardless of the underlying technology. The project distinguishes itself through an extensible, plugin-based architecture that allows for functional expansion and broad support for various database drivers. It integrates advanced workflow automation, enabling users to schedule repetitive tasks and execute complex sequences of operations as background processes. Additionally, the environment incorporates AI-driven assistance for generating SQL queries and executing natural language commands, alongside robust security features such as Kerberos authentication and cloud credential management. Beyond core connectivity, the application offers a comprehensive suite of tools for data analysis, including grid-based editing, schema comparison, and execution plan visualization. Users can manage large datasets efficiently through virtual data paging and customize their workspace with context-aware UI components. The platform also supports automated lifecycle management, allowing for the execution of custom shell commands during connection events to streamline administrative workflows.