Declarative Database Schema Migration Tools

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.

This project is a command-line utility designed to manage database schema versioning and automate incremental schema updates. It functions as a version control system for database structures, ensuring consistency across environments by tracking applied migrations in a dedicated metadata table and executing scripts in a sequential, reliable manner. The tool distinguishes itself through a driver-based abstraction layer that supports a wide range of database engines, including various SQL and distributed cloud databases. It provides robust concurrency control through advisory locking, which prevents conflicting schema changes during simultaneous deployment attempts. To ensure data integrity, the system supports atomic execution by wrapping migration scripts in transactions, while also offering the flexibility to execute custom shell scripts or complex multi-statement files using delimiter-based parsing. The platform includes comprehensive configuration options for managing database connections, retry logic for transient errors, and the customization of migration tracking tables. It is designed to integrate into automated deployment pipelines, providing a unified interface for schema management regardless of the underlying database technology.

Bytebase is a database DevSecOps platform and management console designed to orchestrate schema migrations, deployments, and security audits across multiple database engines. It serves as a SQL GitOps tool that synchronizes database states with configurations stored in Git repositories to manage infrastructure as code. The platform distinguishes itself through a multi-database management console that provides a single interface for relational and NoSQL databases. It includes a security layer for role-based access control, database activity auditing, and column-level data masking to protect sensitive information. The system covers a broad range of capabilities, including automated database migration, declarative schema management, and state-based drift detection. It also provides tools for rule-based SQL linting, batch change execution across multi-tenant environments, and infrastructure as code provisioning. Installation and configuration can be automated on Kubernetes clusters using Helm charts.

Prisma is a type-safe database object-relational mapper that uses a declarative schema to map data models to relational and document databases. It provides a unified toolkit for data access, combining a database driver with tools for schema management and record manipulation. The project features a multi-database driver that standardizes interactions across PostgreSQL, MySQL, and MongoDB. It includes a system for tracking and applying structural schema migrations across different environments and a graphical user interface for browsing and editing database records. The system ensures data integrity through static type generation and a type-safe client, allowing for query execution with automatic type checking. It translates high-level data modeling into physical database tables or collections via a declarative schema definition.

Flyway is a database schema versioning tool and SQL migration orchestrator. It applies version-controlled schema changes to relational databases using SQL scripts and Java Database Connectivity to ensure environments remain consistent and reproducible. The tool tracks applied migration scripts in a dedicated metadata table to determine which updates require execution. It supports the synchronization of schema versions across multiple different database engines and provides integration for build systems and application frameworks to automate updates during software release processes. Capabilities include versioned script execution, dynamic driver loading to extend database connectivity, and configuration via external files. The system also supports orchestrated containerized deployments for database setup.

TypeORM is an object-relational mapper for TypeScript and JavaScript that bridges the gap between object-oriented application code and relational database tables. It provides a comprehensive data persistence layer that allows developers to define database entities using class decorators or configuration objects, enabling seamless interaction with data through object-oriented patterns. The project distinguishes itself through a flexible architecture that supports both the data mapper and repository patterns, alongside a fluent query builder that translates high-level method calls into platform-specific SQL. It includes a robust schema synchronization engine that automatically generates and applies migrations, ensuring that database structures remain consistent with application models. Furthermore, it offers specialized support for hierarchical data modeling, vector similarity search, and cross-database querying, allowing for sophisticated data management across diverse storage engines. Beyond its core mapping capabilities, the framework provides extensive tools for managing database connections, including support for replication, multi-database routing, and atomic transaction management. It also features a lifecycle event system for executing custom logic during data operations, as well as comprehensive performance optimization utilities like relation loading strategies, result caching, and query analysis. The project is designed for cross-platform compatibility, supporting various relational and document-based database drivers in environments ranging from Node.js servers to browser and mobile applications.

Goose is a database schema versioning system and SQL migration tool designed for Go applications. It functions as a framework for tracking and applying incremental database changes through versioned SQL scripts, ensuring consistency across different environments. The project distinguishes itself by providing a build-time capability to exclude unused database drivers to optimize binary size and a filesystem abstraction that allows migration scripts to be bundled directly into a compiled executable. It also supports out-of-order execution logic to apply missing scripts that were created after a newer version was already recorded. The tool covers a broad range of schema evolution capabilities, including forward migrations, rollbacks, and the population of initial reference data through seeding utilities. It manages SQL execution with semicolon-aware statement grouping, transaction-aware processing with manual overrides for non-transactional operations, and the injection of dynamic values via environment variable substitution.

Gel is an object-relational database system that models data as a graph of interconnected objects. By utilizing a strongly typed schema, it enables complex relational queries and polymorphic data structures without the need for traditional join tables. The system integrates native vector storage and similarity search operators, allowing it to function as both a relational and a vector database for semantic data retrieval. The platform distinguishes itself through a comprehensive suite of developer-centric automation tools. It features a declarative migration system that tracks and versions schema changes, supporting advanced workflows like schema branching and merging. To ensure application-level reliability, the database introspects its own schema to generate type-safe client libraries and query builders, providing consistent data structures across application code. Beyond core storage, the system provides extensive capabilities for data modeling, including computed properties, custom scalar types, and complex constraints. It supports versatile query execution, ranging from hierarchical nested data retrieval and atomic transactions to integrated retrieval-augmented generation workflows that connect directly to external language models. The project is managed through a command-line interface that handles the full lifecycle of database instances, including provisioning, monitoring, and automated backup restoration. It offers flexible connectivity options, supporting both native language-specific drivers and a standardized HTTP-based query protocol.

Dbmate is a framework-agnostic SQL database migration tool used for tracking, applying, and rolling back schema changes to ensure consistent environments. It functions as a database schema versioning tool that manages updates independently of any specific application framework by relying on raw SQL and connection URLs. The project distinguishes itself by offering a container-based approach to database administration, allowing schema updates to be executed via Docker to avoid local binary installations. It also supports embedding migration scripts directly into the compiled binary to eliminate external file dependencies during deployment. The tool covers a broad range of database lifecycle management capabilities, including the generation of timestamped migration files, schema exporting, and the ability to poll for database availability. It provides automated version control through state tracking and supports CI/CD integration with features such as sensitive log redaction.

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.

Sequelize is an object-relational mapping library that provides a unified interface for managing relational data through code. By implementing the Active Record pattern, it maps database tables to application objects, allowing developers to perform standard create, read, update, and delete operations using high-level method calls. The library abstracts complex database interactions by translating these calls into optimized, engine-specific SQL statements, ensuring consistent behavior across different database systems. The project distinguishes itself through a comprehensive suite of tools for managing relational complexity and data integrity. It features a robust association system that supports one-to-one, one-to-many, and many-to-many relationships, including polymorphic associations and nested join mapping. To maintain consistency during complex operations, it includes an asynchronous transaction coordinator and a lifecycle management framework that triggers custom logic through hooks and validation rules. Furthermore, it provides a schema synchronization engine that aligns application model definitions with the underlying database structure, supporting versioned migrations to track changes over time. Beyond its core mapping capabilities, the library offers extensive support for database management and performance tuning. This includes connection pooling to manage concurrent requests, read replication for distributed query operations, and query scopes for reusable data retrieval patterns. It also provides native support for TypeScript, allowing for type-safe data definitions and model configurations. The library is designed for modular integration and includes utilities for query logging, custom data type definitions, and soft deletion.

Ent is a statically typed entity framework for Go that models database structures as a graph of nodes and edges. It functions as a code generation engine that transforms schema definitions into type-safe database clients, query builders, and migration scripts. By representing data as interconnected entities, the framework enables intuitive traversal of complex relationships and ensures that database interactions remain consistent with the application model at compile time. The framework distinguishes itself through its graph-based approach to data modeling and its reliance on compile-time code generation to enforce type safety. It automates the synchronization of database schemas with application models, providing tools to manage versioned migrations and validate structural integrity before changes are applied. Developers can customize the generation pipeline using templates to tailor the output to specific infrastructure requirements. Beyond core modeling and generation, the project provides a comprehensive suite of tools for managing the data lifecycle. This includes automated API development for GraphQL, cursor-based pagination for large datasets, and built-in mechanisms for auditing data changes. The system also optimizes data retrieval by automating the loading of related entities, reducing the need for manual query management.

Sea-ORM is an asynchronous SQL object-relational mapper and database toolkit for mapping relational tables to strongly typed objects. It provides a relational database mapper for performing CRUD operations across MySQL, PostgreSQL, and SQLite, and includes a programmatic dynamic query builder for constructing complex SQL statements. The project distinguishes itself by providing a GraphQL schema generator that transforms database entities into typed schemas with built-in pagination and filters. It also features a dedicated database migration tool for defining and applying versioned schema changes. The toolkit covers broad capability areas including relational data modeling and schema management, where it supports the automatic generation of entities from existing database schemas. It further provides advanced query building features such as aggregate value computation, partial model projection, and linked entity fetching, all executed within non-blocking asynchronous runtimes. The project includes a command-line interface for database entity generation and GraphQL server bootstrapping.

Entity Framework Core is an object-relational mapper that enables developers to interact with database systems using strongly-typed code. It serves as a comprehensive data access framework, providing a unified interface for mapping application objects to relational and non-relational database schemas while managing the lifecycle of data operations through a central context. The project distinguishes itself through a provider-based architecture that decouples core data access logic from specific database engines, allowing for consistent interaction across diverse storage systems. It features a sophisticated query translation engine that converts language-integrated queries into optimized, database-specific commands, alongside a robust migration toolset that automates schema evolution by synchronizing the physical database structure with the application model. Beyond its core mapping and query capabilities, the framework provides extensive tooling for database scaffolding, reverse engineering, and automated code generation. It supports complex data modeling requirements, including inheritance hierarchies, owned entity relationships, and custom mapping configurations, while offering built-in mechanisms for transaction management, concurrency control, and connection resiliency. The framework includes comprehensive observability and testing utilities, such as command interception, operation logging, and in-memory database simulation for isolated testing. It is designed for integration with standard dependency injection containers and provides configuration hooks to customize scaffolding and migration logic.

This toolkit provides an asynchronous interface for interacting with relational databases, offering a unified driver-agnostic layer for managing connection pools and executing transactions. It is designed to integrate with asynchronous runtimes, enabling non-blocking database operations while maintaining secure, encrypted communication between the application and the database server. The project distinguishes itself through its compile-time validation capabilities, which use procedural macros to inspect SQL syntax and parameter types against a live database schema during the build process. This approach ensures that queries are verified for correctness before the application is deployed. Additionally, it features automated type mapping that transforms database rows into strongly typed structures, reducing the need for manual data conversion. Beyond its core validation and mapping features, the toolkit supports both dynamic and prepared SQL execution, with transparent caching of execution plans to optimize performance. It also includes a built-in migration manager that allows developers to bundle versioned schema scripts directly into the application binary, ensuring consistent database state management across different deployment environments.

This project is a type-safe database toolkit and object-relational mapper designed to enforce structural consistency between database schemas and application code. By leveraging compile-time validation, it ensures that SQL queries and data structures remain synchronized, preventing common errors before the application executes. It provides a comprehensive framework for relational data modeling, allowing developers to define table associations and map database results directly into strongly-typed language objects. The library distinguishes itself through its focus on compile-time safety and automated schema management. It utilizes procedural macros to inspect database tables and generate corresponding code structures, eliminating the need for manual type definitions. Its expression-based query builder allows for the construction of complex, modular SQL statements that are automatically parameterized to mitigate security risks like SQL injection. Furthermore, the system supports extensive customization, enabling developers to register custom functions and operators or extend the query builder interface to accommodate specific database requirements. Beyond its core mapping and validation capabilities, the toolkit provides a full suite of operations for managing data persistence. This includes support for batch insertions, relational joins, upsert operations, and the retrieval of related records. The library also handles the bidirectional transformation of data, automatically mapping application structures to database columns for updates and insertions while inferring return types for query results. Comprehensive documentation and tooling are provided to assist with schema synchronization, ensuring that local code representations remain aligned with the underlying database throughout the development lifecycle.

EntityFramework is a .NET object-relational mapper that translates application objects into database tables and rows. It functions as a query engine that converts high-level expressions into optimized SQL commands for data retrieval. The project provides a mechanism for monitoring modifications to loaded objects to synchronize application state with the database. It also includes a system for synchronizing database structures with data models using versioned migration scripts. The framework supports multi-backend database integration through a plugin system, allowing a single application to connect to various storage engines. It enables data manipulation using a typed language to perform database lookups and filters.