3 repositorios
Tools and systems for defining custom data structures, schemas, and relational models as code.
Distinguishing note: Focuses on schema-as-code for CRM-style record definitions rather than generic database management or ORM libraries.
Explore 3 awesome GitHub repositories matching data & databases · Data Modeling Frameworks. Refine with filters or upvote what's useful.
Twenty is a headless customer relationship management framework that enables developers to build, version, and deploy custom business applications using code. By utilizing a declarative approach to data modeling, the platform allows for the definition of custom objects, fields, and complex relationships directly within the source code. This schema-driven architecture automatically generates corresponding REST and GraphQL APIs, ensuring that data structures and interface components remain synchronized across development and production environments. The platform distinguishes itself through a m
Adjust the structure of your information tracking to match specific business processes and organizational requirements, ensuring that every field serves a clear purpose for your team.
Vapor is a comprehensive server-side web framework designed for building scalable, high-performance applications and APIs in Swift. It provides a non-blocking, event-loop-based runtime that manages concurrent task processing, background job queues, and asynchronous request handling. The framework is built around a dependency injection container that manages the lifecycle and resolution of services, configurations, and database connections throughout the request pipeline. The framework distinguishes itself through a protocol-oriented design that emphasizes type safety across all layers of the
Define data models by conforming to a protocol and using property wrappers to map class properties to database table fields and unique identifiers.
Cube is a semantic data layer that provides a unified framework for defining business metrics, dimensions, and relationships across diverse data sources. By acting as a headless business intelligence engine, it transforms raw data into a governed model that can be queried via SQL, REST, and GraphQL interfaces. This architecture ensures consistent data definitions and logic across all downstream analytical applications and reporting tools. The platform distinguishes itself through its integrated conversational AI capabilities, which allow users to explore data using natural language. It orches
Provides a code-first environment for defining metrics, dimensions, and relationships across disparate data sources to ensure a single source of truth.